The methods and systems that the computer uses

Abstract

The method for deriving a physiological parameter includes measuring a glucose level of a subject over time, measuring HbA1c of individual red blood cells in a sample comprising a plurality of red blood cells, deriving a measured blood cell HbA1c distribution of the sample, and deriving (a) a red blood cell removal constant (k age ), (b) Erythrocyte glycation rate constant (k gly ), and / or (c) calculating at least one physiological parameter selected from the group consisting of: (a) the apparent glycation constant (K).

Description

[Technical Field]

[0001] [Cross-reference to related applications] This application claims priority to U.S. Provisional Patent Application No. 62 / 939,956 filed November 25, 2019, U.S. Provisional Patent Application No. 63 / 015,044 filed April 24, 2020, and U.S. Provisional Patent Application No. 63 / 081,599 filed September 22, 2020.

[0002] [Description of federally funded research or development] Not applicable [Background technology]

[0003] Measuring various samples within an individual can sometimes be essential for monitoring their health. During normal circulation of red blood cells in mammals like humans, glucose molecules attach to hemoglobin, which is called glycosylated hemoglobin (also known as glycated hemoglobin). The higher the amount of glucose in the blood, the higher the percentage of circulating hemoglobin molecules to which glucose molecules are attached. When diabetes mellitus is not well controlled, the level of glycated hemoglobin in the subject's red blood cells increases. Since glucose molecules remain attached to hemoglobin for the lifespan of red blood cells (usually no longer than about 120 days), the level of glycated hemoglobin reflects the average blood glucose level over this period.

[0004] Most hemoglobin is of a type called HbA. When glucose molecules attach to HbA molecules, glycated HbA called HbA1 is formed. HbA1 has three components: HbA1a, HbA1b, and HbA1c. Since glucose attaches more strongly and to a greater extent to HbA1c than to HbA1a and HbA1b, measuring blood HbA1c (HbA1c test) is often used to indicate the average blood glucose level of a subject over a period of 100-120 days (the average lifespan of red blood cells). The HbA1c test is performed by taking a blood sample from the subject in the doctor's office and then analyzing it in a laboratory. The HbA1c test can be used as a screening and diagnostic test for prediabetes and diabetes. The HbA1c test can be performed multiple times over a period of time to monitor the subject's health toward diagnosis and / or treatment decisions. [Prior art documents] [Patent Documents]

[0005] [Patent Document 1] U.S. Provisional Patent Application No. 62 / 939,956 [Patent Document 2] U.S. Patent Application Publication No. 2018 / 0231573 [Patent Document 3] U.S. Patent No. 6,175,752 [Patent Document 4] U.S. Patent Application Publication No. 2011 / 0213225 [Patent Document 5] U.S. Patent Application Publication No. 2018 / 0235524 [Patent Document 6] U.S. Provisional Patent Application No. 62 / 750,957 [Patent Document 7] U.S. Patent Application Publication No. 2014 / 0188400 [Patent Document 8] U.S. Patent Application Publication No. 2014 / 0350369 [Patent Document 9] U.S. Patent Application Publication No. 2008 / 0009692 [Patent Document 10] U.S. Patent Application Publication No. 2011 / 0319729 [Patent Document 11] U.S. Patent Application Publication No. 2015 / 0018639 [Patent Document 12] U.S. Patent Application Publication No. 2015 / 0025345 [Patent Document 13] U.S. Patent Application Publication No. 2015 / 0173661 [Patent Document 14] U.S. Patent Application Publication No. 2011 / 0193704 [Non-patent literature]

[0006] [Non-Patent Document 1] Lazareva et al., "Biophotonics: Photonic Solutions for Better Health Care VI," SPIE 10685, 1068540 (May 17, 2018). [Non-Patent Document 2] "Glucose management indicator (GMI): A new term for estimating A1C from continuous glucose monitoring," Diabetes 41(11), pp. 2275-2280, November 2018. [Non-Patent Document 3] "Translating the A1C assay into estimated average glucose values," Diabetes Care 31(8) pp. 1473-1478, August 2008, PMID:18540046 [Non-Patent Document 4] "Mechanistic modeling of hemoglobin glycation and red blood cell kinetics enables personalized diabetes monitoring," Sci.Transl.Med.8, 359ra130, October 2016. [Overview of the Initiative] [Problems that the invention aims to solve]

[0007] Commercially available in vitro blood glucose test strips and in vivo sensors (and associated devices and systems) provide glucose level measurements at various measurement frequencies. Furthermore, these devices provide estimated HbA1c ("eHbA1c") values. While both in vitro and in vivo sensors (and associated devices and systems) are known to be reliable and accurate, significant discrepancies have been observed between these two measurements when comparisons have been made between HbA1c and eHbA1c values. Existing eHbA1c methods and devices are generally considered less reliable than HbA1c test results due to their reliance on static models, rough assumptions, and / or less robust data. However, determining HbA1c is inconvenient and unpleasant for subjects who must have their blood drawn regularly for the test and then await the results. In addition, both subjects and healthcare providers would benefit from more accurate eHbA1c, which would allow them to monitor and respond to any changes in eHbA1c. In other words, there is a need for improved eHbA1c methods and devices.

[0008] The following figures are included to illustrate certain aspects of this disclosure and should not be considered exclusive embodiments. The subject matter disclosed can be substantially modified, altered, combined, and equivalent in form and function without departing from the scope of this disclosure. [Brief explanation of the drawing]

[0009] [Figure 1] This diagram shows a flow chart of a non-limiting example of Method 100 of this disclosure. [Figure 2] This figure shows an example of a system for applying physiological parameters determined by the methods described herein, as part of an embodiment of this disclosure. [Figure 3] This figure shows an example of a system for applying physiological parameters determined by the methods described herein, as part of an embodiment of this disclosure. [Figure 4A] This figure shows an example of a method for determining a personalized target glucose range according to some embodiments of the present disclosure. [Figure 4B] This figure shows an example of a personalized-target glucose range report that can be generated as an output by a system according to some embodiments of this disclosure. [Figure 5] This figure shows an example of a personalized-targeted average glucose report that can be generated as output by a system according to some embodiments of this disclosure. [Figure 6] This figure shows an example of a glucose pattern insight report that can be generated as output by a system according to some embodiments of this disclosure. [Figure 7] This figure shows an example of an in vivo sample monitoring system according to some embodiments of the present disclosure. [Modes for carrying out the invention]

[0010] This disclosure describes methods, devices, and systems for determining physiological parameters relating to the kinetics of glycation, removal, and development of red blood cell hemoglobin in a subject's body. Such physiological parameters can be used, for example, to calculate more reliable HbA1c and / or personalized target glucose ranges.

[0011] In this specification, the terms "HbA1c level", "HbA1c value", and "HbA1c" are used interchangeably. In this specification, the terms "aHbA1c level", "aHbA1c value", and "aHbA1c" are used interchangeably. In this specification, the terms "cHbA1c level", "cHbA1c value", and "cHbA1c" are used interchangeably.

[0012] Dynamics model Chemical formula 1 shows the kinetics of erythrocyte hemoglobin glycation (or briefly called erythrocyte glycation in this specification), erythrocyte removal, and erythropoiesis, where "G" in the formula is free glucose, "R" is non-glycated erythrocytes, and "GR" is glycated erythrocyte hemoglobin. The rate at which glycated erythrocyte hemoglobin (GR) is formed is herein referred to as the erythrocyte hemoglobin glycation rate constant (typically in units of dL * mg -1* per day -1 and is also referred to as the erythrocyte glycation rate constant k gly ). Chemical formula 1 TIFF0007891421000001.tif4240

[0013] Over time, erythrocyte hemoglobin containing glycated erythrocyte hemoglobin is constantly removed from the subject's circulatory system, and new erythrocytes containing hemoglobin are generated typically at a rate of about two million per second. The rates for removal and generation are herein referred to as the erythrocyte removal constant (typically in units of per day -1 k age ) and the erythrocyte generation rate constant (typically in units of M 2 / day k gen ), respectively. Since the amount of erythrocytes in the body is maintained at a stable level in most cases, the ratio of k age to k gen can be set as individual constants that are the square of the erythrocyte concentration.

[0014] Regarding glycation, chemical formula 2 illustrates this mechanism in more detail, in which glucose transporter 1 (GLUT1) facilitates the transport of glucose (G) into red blood cells. Subsequently, intracellular glucose (GI) interacts with hemoglobin (Hb) to produce glycated hemoglobin (HbG), in which case the hemoglobin glycation reaction rate constant is k g (typically dL) * mg -1* day -1 It is represented by (which has the unit k). g k is given by equation 1. gly It is associated with, and here k g is, k gly It is an ingredient of [the product]. chemical formula 2 JPEG0007891421000002.jpg22170 formula 1 JPEG0007891421000003.jpg6150 k in the above formula c This is the rate constant for glucose consumption within red blood cells (typically in day 2 -1 (It has the unit V) max This is the maximum glucose transport rate (typically mg * dL -1* day -1 It has the unit (and should be proportional to the GLUT1 level on the membrane, K M k in Equation 1 is the Michaelis-Menten kinetic rate constant (typically having units of mM / dL or mg / dL) for GLUT1, which transports glucose across the red blood cell membrane. gly is dL * mg -1* day -1 It has the unit of [this unit].

[0015] k g and K M k is a value that differs only slightly, even if it does differ between individuals, and therefore, in this specification, we assume it is a constant value. Typical experimental measurement k g The value is 1.2 x 10 -3 The concentration is dL / mg / day. The hemoglobin glycation reaction is a multi-stage non-enzymatic chemical reaction, and therefore, kg K can be considered a universal constant. M K is the Michaelis constant relating to the affinity of an enzyme (e.g., GLUT1) to a substrate (e.g., glucose). M This is determined experimentally. K for RBC GLUT1-glucose interaction M Regarding this, various values ​​ranging from approximately 100 mg / dL to approximately 700 mg / dL have been reported in the literature. Two specific exemplary values ​​are 306 mg / dL and 472 mg / dL.

[0016] As mentioned above, HbA1c is a commonly used metric that indicates the fraction of glycated hemoglobin found in red blood cells. Therefore, a dynamic model can be used, for example, to derive a calculated HbA1c based on at least the glucose level measured for a subject. However, this dynamic model can also be applied to HbA1. For the sake of simplification, this specification will uniformly use HbA1c, but it is considered that HbA1 can be used instead, except in cases where a specific HbA1c value is used. In such cases, a similar formula could be derived using a specific HbA1 value.

[0017] Typically, when modeling physiological processes dynamically, assumptions are made to simplify some of the numerical calculations by focusing on the factors that have the greatest influence on the physiological process.

[0018] This disclosure uses only the following set of assumptions to dynamically model the physiological processes illustrated in Chemical Formulas 1 and 2. First, there are no abnormal red blood cells that are thought to affect HbA1c measurement. Second, the glycation process is first-orderly dependent on the concentrations of both hemoglobin and intracellular glucose in red blood cells, and this assumption is widely adopted. Third, newly formed red blood cells contain only very small amounts of glycated hemoglobin. Finally, red blood cells are removed from circulation when the subject reaches an age specific to the individual. The rate of red blood cell removal in an individual is approximated using a constant. Thus, the rate of glycated hemoglobin removal is proportional to the product of the total red blood cell removal rate and the HbA1c at that point in time.

[0019] Using these assumptions described above for this dynamic model of a single erythrocyte under glucose exposure, the slow conversion from non-glycated hemoglobin (R) to glycated hemoglobin (GR) within the erythrocyte should occur according to Equation 2. formula 2 JPEG0007891421000004.jpg9150 Here, C = [R] + [GR] (Equation 3), or C is the total number of hemoglobin molecules in red blood cells, which typically have a unit of M (moles). Here, [R] and [GR] typically have the unit M (moles), Here, [G] typically has units of mg / dL.

[0020] (a) Assuming that the glucose level is constant and the concentrations of glycated and non-glycated red blood cells remain stable (d[GR] / dt=(d[R]) / dt=0), and (b) H(0) is 0% because the red blood cells were not exposed to glucose, equations 4 and 5 can be derived. Furthermore, equation 5 is k gly And [G] can be considered constant in the steady state, so it can be generalized to Equation 6. formula 4 In the above formula, H is the HbA1c value of a single red blood cell in units of %, t is the age of the red blood cell in units of days, and [GI] is the intracellular glucose concentration in units of mg / dL. formula 5 JPEG0007891421000006.jpg6150 formula 6 JPEG0007891421000007.jpg6150

[0021] Therefore, the age (t) of a red blood cell is proportional to the HbA1c value of that red blood cell. The relationship between blood cell age and HbA1c value is given by Equation 4. Under variable glucose, Equation 4 becomes Equation 7 for a single red blood cell. formula 7 JPEG0007891421000008.jpg7150 In the above formula, AGI(t) is the cumulative average intracellular glucose up to time t.

[0022] Therefore, Equation 8 is the HbA1c value of red blood cells on day i, and Equation 9 is the intracellular glucose concentration ([GI]). formula 8 JPEG0007891421000009.jpg6150 Here, The filename is JPEG0007891421000010.jpg10150. formula 9 JPEG0007891421000011.jpg6150 Here, g=(K M * [G]) / (K M It is +[G]).

[0023] Furthermore, assuming that the age distribution p(d) for red blood cells is a combination of fixed lifespan and random removal, this distribution follows Equation 10. Formula 10 JPEG0007891421000012.jpg15150d≧A max When this is the case, p(d)=0. Here, The image is JPEG0007891421000013.jpg14150, where T is an individual, unitless constant that must be greater than 0 and less than 1, and d is the age in days.

[0024] The fraction of red blood cells on day i (F(i)) is derived from equation 10 to obtain equation 11. Formula 11 JPEG0007891421000014.jpg6150 Here, The filename is JPEG0007891421000015.jpg13150.

[0025] When a fixed lifespan is assumed for red blood cells, formula 12 can be used instead of formulas 10 and 11 in the methods and systems described herein. Formula 12 JPEG0007891421000016.jpg12150 JPEG0007891421000017.jpg6150

[0026] The method disclosed herein utilizes the above-described relationship to obtain the rate constant k age and k gly We derive K(k gly / k age (Apparent glycation constant equal to) and k gen Derive the following.

[0027] Figure 1 shows a non-limiting example of method 100 of the present disclosure. To give [G] as a function of t ([G](t)102), the subject (also referred to herein as the patient) is measured over a period of time (e.g., one month or longer). [G](t)102 is k gly It can be converted to [GI] as a function of t ([GI](t)104) using the formula. [GI](t)104 can be converted to an HbA1c value as a function of blood cell age (H(i)106, formula 8). Separately, the age distribution of red blood cells (F(i)108, formula 11 and / or formula 12) is k age It is associated with H(i)106 and estimated k derived from glucose level measurements. age Using F(i)108 based on this, the derived individual blood cell HbA1c distribution110 (mathematical representation such as a plot, equation, and table) is obtained, which represents the number of individual red blood cells with a specific HbA1c value. More specifically, an HbA1c value is assigned to each individual red blood cell in F(i)108 by H(i)106.

[0028] Furthermore, in order to give a measured individual blood cell HbA1c distribution 112 that is compared with the derived individual blood cell HbA1c distribution 110, the HbA1c values ​​for individual red blood cells in the patient sample are measured. Then, in order to improve the fit of the derived individual blood cell HbA1c distribution 110 to the measured individual blood cell HbA1c distribution 112, k age and k g (or kgly ) is repeatedly regulated.

[0029] Subsequently, the dynamic constant k for each individual is determined. age , k gly , and K(k gly / k age The apparent glycation constant (equal to) is, (a) Calculated HbA1c, (b) Corrected HbA1c, (c) Personalized - Target glucose range, (d) Personalization - Target average glucose, (e) Personalized treatment for subject triage, (f) Personalized treatment for the titration of diabetes medications, (g) Personalized closed-loop or hybrid closed-loop control systems, (h) Personalized treatment using glycation drugs, (i) Identification of abnormal or pathological physiological conditions, (j) Identification of nutritional supplements and / or drugs present during the test, and (k) Determination of physiological age, It can be applied to a variety of uses, including but not limited to these.

[0030] Furthermore, one or more of (a) to (k) can be used as a basis for administering and / or modifying a patient's treatment. Such treatments may include, but are not limited to, insulin administration, glycation drug administration, exercise regimens, dietary intake, or combinations thereof. Generally, the administration and / or modification of such treatments will be based on current treatments, but it is conceivable to use individual values ​​of (a) to (k) rather than the aforementioned values ​​currently used as a basis for such treatments.

[0031] Individual blood cell HbA1c measurement For example, the HbA1c value for individual red blood cells can be determined using spectroscopic techniques such as fluorescence, refractive index measurement, and Raman spectroscopy, as described in Lazareva et al., "Biophotonics: Photonic Solutions for Better Health Care VI," SPIE 10685, 1068540 (May 17, 2018). Of the above, fluorescence is preferred because flow hemocytometry can be used to rapidly and accurately measure the fluorescence emission of individual blood cells. More specifically with respect to fluorescence, hemoglobin excited at 160 nm or 270 nm has different emission wavelengths depending on whether it is glycated (HbA1c) or unglycated (Hb). Therefore, the HbA1c level in individual blood cells is proportional to the intensity of the emitted fluorescence. Flow hemocytometry can measure the fluorescence emission of individual blood cells. Therefore, flow erythrocyte counting methods with excitation wavelengths of 160 nm or 270 nm provide a measure of the individual HbA1c values ​​of multiple blood cells in a blood sample or a distribution of the individual HbA1c values ​​of blood cells.

[0032] In another example, the HbA1c value for individual red blood cells can be determined using an HbA1c-specific fluorescently tagged antibody (fluorescent HbA1c antibody). In summary, the blood cells are stabilized, infiltrated, and stained with a fluorescent HbA1c antibody and a fluorescent RNA marker (in this case, the fluorescent HbA1c antibody and the fluorescent RNA marker emitting different wavelengths) and analyzed by flow hemocytometry as described in U.S. Patent Application No. 2018 / 0231573, which is incorporated herein by reference.

[0033] While this specification describes flow hemocytometry as preferred for reasons of high throughput, short sample analysis time, and accuracy, other methods for measuring HbA1c values ​​for individual red blood cells may be used in the methods and systems described herein.

[0034] Measurement of glucose levels The glucose level measurements described herein can be performed using in vivo and / or in vitro (extra vivo) methods, devices, or systems for measuring glucose in at least one sample, such as glucose in a body fluid, such as blood, interstitial fluid (ISF), subcutaneous fluid, dermal fluid, sweat, tears, saliva, or other biological fluids. In some cases, in vivo methods, devices, or systems can be used in combination with in vitro methods, devices, or systems.

[0035] Examples of in vivo methods, devices, or systems measure glucose levels in blood or ISF and optionally other specimens, provided that at least a portion of a sensor and / or sensor-control device is positioned or can be positioned on the subject's body (e.g., beneath the subject's skin surface). Examples of devices include, but are not limited to, continuous specimen monitoring devices and intermittent specimen monitoring devices. Specific devices or systems are described further herein and can be found in U.S. Patent No. 6,175,752 and U.S. Patent Application Publication No. 2011 / 0213225, the entire disclosures of each of these documents are incorporated herein by reference for all purposes.

[0036] In vitro methods, devices, or systems (including entirely non-invasive ones) include sensors that come into contact with body fluids outside the body to measure glucose levels. For example, an in vitro system may use a measuring device that holds a subject's body fluids and has a port for receiving a sample test strip that can be analyzed to determine the glucose level inside. Additional devices and systems are described further below.

[0037] The frequency and duration of glucose level measurements can vary on average from about 3 times a day (e.g., every 8 hours) to about 14,400 times a day (e.g., every 10 seconds) (or more frequently), and from a few days to about 300 days.

[0038] With glucose levels measured, these are used in combination with the measured HbA1c distribution of individual blood cells to determine one or more physiological parameters (k gly , k age , and / or K) and optionally other analytical results (e.g., cHbA1c, aHbA1c, personalized-target glucose range, and others as described herein) can be determined. In some cases, such analysis can be performed by a physiological parameter analysis system. For example, in some embodiments, the glucose monitor may include a glucose sensor which (1) processes the signal from the glucose sensor and (2) is coupled to an electronic device for communicating the processed glucose signal to one or more of the health monitoring device, server / cloud, and data processing terminal / PC.

[0039] With glucose levels measured, one or more physiological parameters and optionally other analytical results described herein can be determined. In some cases, such analyses can be performed by a physiological parameter analysis system. For example, in some embodiments, the HbA1c distribution of individual blood cells can be measured by laboratory testing, in which case the results are entered into a server / cloud, a patient interface, and / or display from the testing body, a healthcare professional, a subject, or another user. The HbA1c distribution of individual blood cells can then be received by one or more of the health monitoring device, a server / cloud, and a data processing terminal / PC for analysis by one or more of the methods described herein.

[0040] system In some embodiments, one or more physiological parameters (k) determined by the method described herein gly , k age , and / or K) can be applied to the system.

[0041] Figure 2 shows an example of a system 210 for using one or more physiological parameters according to some embodiments of the present disclosure. The system 210 includes one or more processors 212 and one or more machine-readable storage media 214. The one or more machine-readable storage media 214 include an instruction set for performing analysis routines executed by one or more processors 212.

[0042] In some embodiments, the instruction is input 216 (for example, one or more physiological parameters (k) determined as described herein). gly , k age The steps include receiving input 216, and / or K), and optionally one or more glucose levels, one or more HbA1c values, one or more other subject-specific parameters, and / or one or more times associated with any of these; determining output 218 (e.g., errors associated with one or more physiological parameters and one or more parameters or characteristics relating to the subject's personalized diabetes management (e.g., among the parameters or characteristics, particularly cHbA1c, aHbA1c, personalized-target glucose range, mean target glucose level, nutritional supplement or drug dosage)); and communicating output 218. In some embodiments, communication of input 216 may be, for example, through a user interface (which may be part of a display), a data network, a server / cloud, another device, a computer, or any combination thereof. In some embodiments, communication of output 218 may be, for example, to a display (which may be part of a user interface), a data network, a server / cloud, another device, a computer, or any combination thereof.

[0043] As used herein, “machine-readable medium” includes any mechanism capable of storing information in a form accessible by a machine (a machine can be, for example, a computer, a network device, a cellular telephone, a personal digital assistant (PDA), a manufacturing tool, or any device having one or more computers). For example, machine-accessible medium includes recordable / non-recordable medium (for example, read-only memory (ROM), random-access memory (RAM), magnetic disk storage media, optical storage media, and flash memory devices).

[0044] In some cases, one or more processors 212 and one or more machine-readable storage media 214 can reside in a single device (e.g., a computer, network device, cellular phone, PDA, and specimen monitor).

[0045] In some embodiments, such a system may include other components. Figure 3 shows another example of a system 310 for applying physiological parameters according to some embodiments of the present disclosure.

[0046] System 310 includes a health monitoring device 320 having a subject interface 320A and an analysis module 320B, the health monitoring device 320 being or capable of being operationally coupled to a data network 322. Furthermore, within System 310 are provided a glucose monitor 324 (e.g., an in vivo and / or in vitro (ex vivo) device or system) and a data processing terminal / personal computer (PC) 326, each operationally coupled to the health monitoring device 320 and / or the data network 322. Figure 3 further shows a server / cloud 328 operationally coupled to the data network 322 for bidirectional data communication with one or more of the health monitoring device 320, the data processing terminal / PC 326, and the glucose monitor 324. System 310 within this disclosure may exclude one or more of the server / cloud 328, the data processing terminal / PC 326, and / or the data network 322.

[0047] In certain embodiments, the analysis module 320B analyzes one or more physiological parameters (k) determined as described herein. gly , k age The analysis module 320B is programmed or configured to perform an analysis at least in part based on (for example, determining values ​​for cHbA1c, aHbA1c, personalized-target glucose range, and others as described herein, or determining whether the values ​​are outside of specific limit values ​​for these). As shown in the figure, the analysis module 320B is part of the health monitoring device 320 (for example, executed by its internal processor). Alternatively, the analysis module 320B can be associated with one or more of the server / cloud 328, glucose monitor 324, and / or data processing terminal / PC 326. For example, one or more of the server / cloud 328, glucose monitor 324, and / or data processing terminal / PC 326 may have one(s) machine-readable storage media having an instruction set that causes one or more processors to execute an instruction set corresponding to the analysis module 320B.

[0048] The health monitoring device 320, data processing terminal / PC 326, and glucose monitor 324 are shown as being operationally coupled to the data network 322 for communication to and from the server / cloud 328, however, one or more of the health monitoring device 320, data processing terminal / PC 326, and glucose monitor 324 can be programmed or configured to bypass the data network 322 and communicate directly with the server / cloud 328. The mode of communication between the health monitoring device 320, data processing terminal / PC 326, and glucose monitor 324 and the data network 322 includes one or more wireless, wired, RF, BLUETOOTH®, WiFi data, RFID-enabled, ZIGBEE®, or any other suitable data communication protocol, and optionally supports data encryption / decryption, data compression, and data decompression.

[0049] The analysis can be performed by one or more of the following: health monitoring device 320, data processing terminal / PC 326, glucose monitor 324, and server / cloud 328, and the resulting analysis output is shared within system 310.

[0050] Furthermore, although the glucose monitor 324, health monitoring device 320, and data processing terminal / PC 326 are shown as being operationally coupled to each other via a communication link, they can be modules within a single integrated device (e.g., a sensor having a processor and communication interface for transmitting / receiving and processing data).

[0051] Calculation HbA1c (cHbA1c) 1 or more physiological parameters (k gly , k age After calculating HbA1c (K), and / or K), multiple glucose measurements can be obtained over a subsequent period and used to calculate HbA1c during and / or at the end of this period.

[0052] Assuming a steady state where glucose levels are constant and the concentrations of glycated and non-glycated red blood cells remain stable (d[GR] / dt=(d[R]) / dt=0), the following two equations can be derived. Equation 13 gives k as the apparent glycation constant K (typically having units of dL / mg). gly and k age The ratio is defined as such, and Equation 14 establishes the dependence between the rate of red blood cell production and the rate of red blood cell removal. formula 13 JPEG0007891421000018.jpg6150 formula 14 JPEG0007891421000019.jpg6150 Here, g=(K M * [G]) / (K M It is +[G]).

[0053] For the purpose of simplification, the following describes the methods, devices, and systems of this disclosure. age Use k. Unless otherwise specified, gen Instead of k age k can be used. gen Instead of k age In order to use, equation 14 is k gen =k age * C 2 It will likely be rewritten.

[0054] HbA1c is the fraction of glycated hemoglobin, as shown in Equation 15. formula 15 JPEG0007891421000020.jpg6150

[0055] Under the hypothetical state that an individual maintains the same glucose level indefinitely, the HbA1c in Equation 15 can be defined as "equilibrium HbA1c" (EA) (typically reported as a percentage (e.g., 6.5%), but calculations use a decimal type (e.g., 0.065)). For a given glucose level, EA (Equation 16) can be derived from Equations 3, 13, and 15. formula 16 JPEG0007891421000021.jpg6150

[0056] EA is an estimate of HbA1c based on a constant glucose concentration [G] over a long period. This relationship substantially approximates the average glucose and HbA1c for individuals with a stable daily glucose profile.

[0057] Therefore, the average of the glucose levels over time can be used to determine [AG]. The k calculated above age and k gly The steady-state calculation HbA1c(cHbA1c) can be obtained by using (or K) and [AG] according to Equation 17. formula 17 JPEG0007891421000022.jpg6150

[0058] A patient's average daily glucose level may change over time. Therefore, cHbA1c can be calculated using Equation 18. formula 18 JPEG0007891421000023.jpg14150 Here, The filename is JPEG0007891421000024.jpg6170.

[0059] In Equation 18, HbA1c0 is the previously measured HbA1c value. If the time since the last HbA1c test is divided into equal intervals, each usually no longer than one day, then G i and t i θ is the average glucose and time duration within a given interval.

[0060] More frequent glucose monitoring and longer monitoring periods can provide a more accurate cHbA1c result.

[0061] In some cases, the effectiveness of a subject's personalized diabetes management can be monitored by comparing cHbA1c to past cHbA1c and / or previously measured HbA1c (or corrected HbA1c as further described herein). For example, when a diet plan and / or exercise plan is implemented as part of a subject's personalized diabetes management under conditions equal to all other factors (e.g., medications and other diseases), a change in cHbA1c compared to previous cHbA1c values ​​and / or previously measured HbA1c values ​​can indicate whether this diet plan and / or exercise plan is effective, ineffective, or somewhere in between.

[0062] In some cases, cHbA1c is compared to a previous cHbA1c and / or a previously measured HbA1c (or a corrected HbA1c as described herein) using the method described herein. age and k gly It is possible to determine whether or not a new k is derived and / or whether or not an HbA1c measurement is obtained. For example, in the absence of a significant change in the glucose profile, a change in cHbA1c of 0.5 percent or more compared to a previous cHbA1c value and / or a previously measured HbA1c value (or corrected HbA1c as described in more detail herein) (e.g., a change from 7.0% to 6.5% or from 7.5% to 6.8%) is derived by the method described herein. age Value and k gly The steps for deriving the value and / or obtaining the HbA1c measurement can be triggered.

[0063] In some cases, comparison of the cHbA1c with previous cHbA1c values and / or previous measured HbA1c values (or corrected HbA1c as described in more detail herein) can indicate whether abnormal or pathological physiological conditions exist. For example, if a subject has maintained cHbA1c values and / or measured HbA1c values (or corrected HbA1c as described in more detail herein) over a long period of time and then a change in cHbA1c is identified without any other obvious reason, the subject may have a new abnormal or pathological physiological condition. Signs of a new abnormal or pathological physiological condition can be collected from one or more physiological parameters (k gly 、k age 、and / or K). Details of abnormal or pathological physiological conditions regarding one or more physiological parameters will be discussed later herein.

[0064] Regulatory HbA1c In the technical fields of diabetes and erythrocyte hemoglobin glycosylation, the generally accepted average RBC lifespan can vary. k ref age preferably reflects a reference average RBC lifespan from 85 days to 135 days, from 85 days to 110 days, from 90 days to 110 days, from 95 days to 125 days, or from 110 days to 135 days, although the reference RBC lifespan can be outside these ranges. Most preferably, k ref age reflects a reference RBC lifespan from 85 days to 110 days or from 90 days to 110 days, or 100 days. In this specification, for all examples k ref age is equal to 0.01 days -1 . However, embodiments of the present disclosure are not limited to this particular k ref age .

[0065] The aHbA1c for a subject can be calculated by Equation 19 using the HbA1c level for the subject and k age and k ref age . formula 19 In the above formula, HbA1c may be cHbA1c or laboratory-measured HbA1c as described herein.

[0066] Usually K=k gly / k age This requires only one data section to make a decision with high confidence. A larger K value is usually better than a smaller K value. age Since it correlates with the value, k age K can be used to generate a rough aHbA1c early in data acquisition when it is still unavailable (Equation 20). Typical K ref The value is, for example, 5.2 × 10 -4 It is dL / mg. However, embodiments of this disclosure refer to this particular K ref Not limited to this. formula 20 In the above formula, HbA1c may be cHbA1c or laboratory-measured HbA1c as described herein.

[0067] Subsequently, aHbA1c (based at least in part on measured HbA1c and / or calculated HbA1c) for a subject can be used for the subject's diagnostic, treatment, and / or monitoring protocols. For example, a subject can be diagnosed as having diabetes, prediabetes, or another abnormal or pathological physiological condition based at least in part on the aHbA1c described herein. In another embodiment, a subject can be monitored and / or treated by means of self-monitoring and / or self-injection of insulin and continuous monitoring and / or injection of insulin, etc., based at least in part on the aHbA1c described herein. In yet another example, aHbA1c as described herein can be used to determine and / or administer personalized treatment for subject triage, to determine and / or administer personalized treatment for the titration of antidiabetic drugs, to determine and / or administer personalized closed-loop or hybrid closed-loop control systems, to determine and / or administer personalized treatment using glycation agents, to determine physiological age, to identify whether and / or which nutritional supplements and / or drugs are present during a test, and for similar purposes and any combination thereof.

[0068] By eliminating interference caused by differences in RBC turnover rate, aHbA1c is a superior individual biomarker than HbA1c regarding the risk of complications in people with diabetes. aHbA1c may be higher or lower than measured HbA1c, leading to significant differences in the diagnosis and management of diabetes. In individuals with a faster-than-normal RBC turnover rate, HbA1c, which is a typical observed value in patients with kidney disease or after heart valve surgery, may be unnaturally low, giving people the illusion of good blood glucose control. Conversely, a slower-than-normal RBC turnover can lead to unnaturally high HbA1c and overtreatment, potentially resulting in dangerous hypoglycemia.

[0069] For example, 0.0125 days -1 k age(Or an RBC lifespan of 80 days) and a measured HbA1c of 7% are thought to result in an aHbA1c of 8.6%. A measured HbA1c of 7% without adjustment for RBC turnover rate indicates good blood glucose control. However, this HbA1c value is an underestimation, and in this case, a more accurate value of 8.6% (aHbA1c) adjusted for RBC turnover rate indicates a higher risk of complications for the subject.

[0070] In another example, 0.0077 days -1 k age (Or a 130-day RBC lifespan) and a seemingly high measured HbA1c of 9% are thought to result in an aHbA1c of 7.1%. A seemingly high measured HbA1c of 9% is thought to indicate inadequate blood glucose control and a significant risk of complications. However, with an aHbA1c of 7.1%, this person has only a low risk of complications. Proceeding from the measured HbA1c value of 9%, since the aHbA1c is 7.1%, it is thought that the subject is likely to receive treatment that may expose them to the risk of hypoglycemia.

[0071] aHbA1c can be estimated using Equation 20 only when K is available. For example, if the measured HbA1c is 8%, then 6 × 10 -4 day -1 When such a high K value is determined, the estimated aHbA1c value is 7%. This adjustment is usually conservative, and therefore, k age It is safe to use when other options are still unavailable. In this example, unnecessary and potentially harmful treatments may be administered based on measured HbA1c levels when treatment should not be provided based on the aHbA1c level.

[0072] In another example, the measured HbA1c was 7%, and 4 × 10 -4 day -1 When such a low K value is determined, the estimated aHbA1c is 8.9%. In this case, treatment may not be administered if only the measured HbA1c value is used as the basis, but treatment should be provided due to the high aHbA1c.

[0073] k in this specification ref age k is a predetermined value used as the reference mean RBC turnover rate, which represents the RBC lifespan. The RBC turnover rate is k age To give it a unit of 1% per day, divide 1 by the RBC lifetime. * 100 (or k age =(1 / RBC life) * 100) k ref age This is calculated using the same method with the desired standard mean RBC lifetime.

[0074] The subject's k age This can be determined by a variety of methods, including but not limited to those described in U.S. Patent Application Publication No. 2018 / 0235524, U.S. Provisional Patent Application No. 62 / 750,957, and U.S. Provisional Patent Application No. 62 / 939,956, the entire contents of each of these documents are incorporated herein by reference for all purposes.

[0075] HbA1c can be calculated based at least in part on laboratory measurements and / or glucose monitor data (e.g., as described above as cHbA1c). Preferably, this glucose monitor data is continuous with virtually no missing readings to give higher accuracy to the calculated HbA1c level. In this specification, HbA1c is described as calculated HbA1c, although in the art HbA1c level may be referred to as calculated HbA1c level or estimated HbA1c level.To calculate (or estimate) HbA1c levels, you can use the eAG / A1C Conversion Calculator provided by the American Diabetes Association, the Glucose Management Indicator (GMI) method (e.g., "Glucose management indicator (GMI): A new term for estimating A1C from continuous glucose monitoring," Diabetes 41(11) pp. 2275-2280, November 2018), the method described in "Translating the A1C assay into estimated average glucose values," Diabetes Care 31(8) pp. 1473-1478, August 2008 PMID:18540046), or "Mechanistic modeling of hemoglobin glycation and red blood cell kinetics enables personalized diabetes." Several methods can be used, including but not limited to those described in "monitoring (mechanistic modeling of hemoglobin glycation and red blood cell dynamics enables individual diabetes monitoring)," Sci.Transl.Med.8, 359ra130, October 2016, U.S. Patent Application Publication No. 2018 / 0235524, U.S. Provisional Patent Application No. 62 / 750,957, and U.S. Provisional Patent Application No. 62 / 939,956, etc., and any hybrid thereof. The entire contents of each of the aforementioned patent applications are incorporated herein by reference for all purposes.

[0076] The method disclosed herein comprises the steps of determining the HbA1c level of a subject (e.g., by measuring and / or calculating based on a glucose monitor) and determining the RBC removal rate constant (RBC turnover rate and k) of the subject. ageAlso known as, typically Japanese -1 The steps to determine the units of HbA1c and k age Standard k established as age (k ref age The process includes the step of calculating an adjusted HbA1c value (aHbA1c) for the subject based on the following: The subject can then be diagnosed, treated, and / or monitored based on the aHbA1c.

[0077] Non-limiting exemplary methods of this disclosure include the steps of providing (or taking) a number of blood glucose measurements for a subject, calculating an HbA1c for the subject based at least in part on the number of blood glucose measurements, and k age The steps of providing (or determining) and HbA1c level and k age and k ref age The procedure may include a step of calculating aHbA1c for the subject based on the following: The subject can then be diagnosed, treated, and / or monitored based on the aHbA1c.

[0078] Another non-limiting exemplary method of this disclosure is a step of providing (or measuring) HbA1c to a subject and k age The stage of providing (or determining) and HbA1c level and k age and k ref age The procedure may include a step of calculating aHbA1c for the subject based on the following: The subject can then be diagnosed, treated, and / or monitored based on the aHbA1c.

[0079] Personalization - Target glucose range and personalized glucose levels Typically, glucose levels in subjects with diabetes are preferably maintained between 70 mg / dL and 180 mg / dL. However, the dynamics model described herein states that when intracellular glucose levels are k glyThis indicates that it depends on physiological parameters such as [specific parameters]. Furthermore, intracellular glucose levels are associated with hypoglycemic and hyperglycemic damage to organs, tissues, and cells. Therefore, measured glucose levels may not actually correspond to the actual physiological conditions related to diabetes management in the subject. For example, higher than normal k[0] gly In subjects with this condition, glucose is absorbed more easily into the cells. Therefore, a measured glucose level of 180 mg / dL is excessively high for this subject and may further prolong the subject's diabetes in the long term. In another example, a lower-than-normal k gly Subjects with this condition do not absorb much glucose into their cells. Therefore, at a glucose level of 70 mg / dL, the intracellular glucose level of the subject is quite low, which can cause weakness and, in the long term, lead to hypoglycemia.

[0080] In this specification, with respect to glucose readings and / or the corresponding personalized glucose range, subject-specific k gly There are three ways to accept this, namely (a) setting the upper and lower limits of the acceptable normal glucose to k gly The system provides (b) a step of adjusting the subject's measured glucose level to reach a target glucose range, (c) a step of adjusting the subject's measured glucose level with respect to an effective plasma glucose level correlated with the upper and lower limits of acceptable normal glucose, and (d) a step of adjusting the subject's measured glucose level with respect to an intracellular glucose level correlated with the lower limit of acceptable normal intracellular glucose (LIGL) and the upper limit of acceptable normal intracellular glucose (UIGL).

[0081] Firstly, using the acceptable lower limit of normal glucose (LGL) and the acceptable upper limit of normal glucose (AU), we can derive equations for the personalized lower limit of glucose (GL) (Equations 21 and 22) and equations for the personalized upper limit of glucose (GU) (Equations 23 and 24). Equations 22 and 24 are rewrites of Equations 21 and 23 for cases where both measured HbA1c and aHbA1c are available. formula 21 JPEG0007891421000027.jpg18150 in the above formula JPEG0007891421000028.jpg7150 is a normal individual k gly And, JPEG0007891421000029.jpg6150 is the subject's k gly That is the case. formula 22 JPEG0007891421000030.jpg10150 formula 23 JPEG0007891421000031.jpg18150 formula 24 JPEG0007891421000032.jpg10150

[0082] Since the upper and lower limits of the glucose range are based on equivalent intracellular glucose levels, equations 21 and 23 are given by k gly It is based on this.

[0083] The current acceptable value for the above is LGL = 70 mg / dL. JPEG0007891421000033.jpg7150=6.2*10 -6 dL * mg -1* day -1 , and AU = 180 mg / dL.

[0084] Figure 4A shows an example of a method for determining a personalized target glucose range 430. The desired glucose range 432 (e.g., the current acceptable glucose range) has a lower limit 434 and an upper limit 436, and is determined by the physiological parameter k gly438 can be used and personalized using formulas 21 and 23, respectively. This results in a personalized glucose lower limit (GL) 440 (formula 21 ± 7%) and a personalized glucose upper limit (GU) 442 (formula 23 ± 7%) that define the personalized target glucose range 430. Alternatively or in addition to the above, a desired glucose range 432 (e.g., the current acceptable glucose range) having a lower limit 434 and an upper limit 436 can be personalized using measured HbA1c and aHbA1c 438 and using formulas 22 and 24, respectively. Thus, the method is generally (a)k gly After calculating (b) and / or after measuring HbA1c and calculating aHbA1c, a personalized target glucose range can be determined, in which case the lower glucose limit can be changed according to formula 21 (and / or formula 22) ± 7%, and / or the upper glucose limit can be changed according to formula 23 (and / or formula 24) ± 7%. For example, 5.5 * 10 -6 dL * mg -1* day -1 Subjects with this condition may have a personalized target glucose range of approximately 81±7 mg / dL to approximately 219±27 mg / dL. Therefore, these subjects may have a different range of acceptable glucose levels than the glucose range currently being treated.

[0085] Figure 4B, with reference to Figure 2, shows an example of a personalized-target glucose range report that can be generated as output 218 by the physiological parameter analysis system 210 of this disclosure. The illustrative report shown includes a plot of glucose levels over a day with respect to the personalized-target glucose range (shaded area) described above. Alternatively, other reports may include, but are not limited to, a free-moving glucose profile (AGP) plot and a numerical representation of the personalized-target glucose range with recent glucose level measurements, and any combination thereof.

[0086] In another example, 6.5*10 -6dL*mg -1 *day -1 k gly Subjects with this condition may have a personalized target glucose range of approximately 66 ± 5.5 mg / dL to approximately 167 ± 18 mg / dL. Due to the considerably lower upper limit of glucose levels, personalized diabetes management for these subjects may involve more frequent glucose level measurements and / or medication administration to substantially keep them within this personalized target glucose range.

[0087] In yet another example, 5.0 * 10 -6 dL * mg -1* day -1 k gly Subjects with this condition may have a personalized target glucose range of approximately 92±8 mg / dL to approximately 259±34 mg / dL. These subjects are more sensitive to lower glucose levels and may experience weakness, hunger, dizziness, etc., more frequently when using the currently administered glucose ranges (70 mg / dL and 180 mg / dL).

[0088] All of the above examples include a personalized lower limit and a personalized upper limit of glucose. However, instead, the personalized-target glucose range may include only the personalized lower limit or the personalized upper limit of glucose, and the other value of the personalized-target glucose range may be the currently administered glucose lower limit or glucose upper limit.

[0089] Subject-specific k with respect to glucose readings and / or corresponding personalized glucose ranges gly A second method for considering this involves using available plasma glucose (PG). eff To achieve the required level, the subject's plasma glucose level (for example, measured using a sample sensor configured to measure glucose levels in body fluids, which in this case can be part of a larger system) is k gly It is then personalized by formula 16. formula 16 JPEG0007891421000034.jpg1135 Here, The filename is JPEG0007891421000035.jpg1115.

[0090] PG eff The levels can be used in combination with the tolerable normal glucose lower limit and / or tolerable normal glucose upper limit to diagnose, monitor, and / or treat subjects. That is, PG eff The level is considered to be between 70 mg / dL and 180 mg / dL in this specification, but should be interpreted in comparison to the tolerable glucose limit, which may change based on new clinical and / or scientific data, as well as recommendations from health authorities.

[0091] For example, 6.5 * 10 -6 dL * mg -1* day -1 k gly A subject with [specific condition] may receive a measured glucose level of 170 mg / dL, which changes to 183 mg / dL when Equation 16 is applied. This value is interpreted based on the tolerable glucose limit (70 mg / dL to 180 mg / dL). Therefore, at this point, the subject would likely consider the measurement of 170 mg / dL to be within the tolerable limit. However, the actual available plasma glucose level is higher, which can affect the appropriate dosage of insulin or other medications delivered.

[0092] Subject-specific k with respect to glucose readings and / or corresponding personalized glucose ranges gly A third method for considering this is that the subject's plasma glucose level (e.g., measured using a sample sensor configured to measure glucose levels in body fluids, which in this case can be part of a larger system) is considered in relation to the intracellular glucose (IG) level. gly It is then personalized by Equation 17. formula 17 JPEG0007891421000036.jpg1125

[0093] Next, the subject's IG level can be compared to the lower limit of acceptable normal intracellular glucose (LIGL) and the upper limit of acceptable normal intracellular glucose (UIGL). The current acceptable values ​​for LIGL and UIGL are 0.29 mg / dL and 0.59 mg / dL, respectively.

[0094] Personalized target glucose ranges and / or personalized glucose levels (e.g., effective plasma glucose levels or intracellular glucose levels) can be determined and / or performed within a physiological parameter analysis system. For example, a set of instructions or programs attached to a glucose monitor and / or health monitoring device that determines therapy (e.g., insulin dosage) can use personalized target glucose ranges and / or personalized glucose levels in such analysis. In some cases, a display or associated subject interface can display personalized target glucose ranges and / or personalized glucose levels.

[0095] Personalized target glucose ranges and / or personalized glucose levels can be updated over time when one or more physiological parameters are recalculated.

[0096] Personalized target glucose ranges can be determined and / or performed within a physiological parameter analysis system. For example, a set of instructions or programs associated with a glucose monitor and / or health monitoring device that determines therapy (e.g., insulin dosage) can use the personalized target glucose range for such analysis. In some cases, a display or associated subject interface can display the personalized target glucose range.

[0097] Personalized target glucose ranges can be updated over time when one or more physiological parameters are recalculated.

[0098] Personalized Target Average Glucose Using Equation 27, the personalized target mean glucose level (GT) can be calculated from the reference glucose target RG. The reference target glucose can be any value that the physician deems appropriate, for example, 120 mg / dL. formula 27 JPEG0007891421000037.jpg18150

[0099] Instead of or in combination with Equation 27, GT can be calculated using Equation 28, which is based on measured HbA1c and aHbA1c. formula 28 JPEG0007891421000038.jpg16170

[0100] Equation 29 can be used to calculate GT when the target HbA1c value (AT) is known, instead of or in combination with Equation 27 and / or Equation 28. formula 29 JPEG0007891421000039.jpg11170

[0101] In some embodiments, the physiological parameter analysis system can determine the average glucose level for the subject during period 208 and optionally display the average glucose level and / or target average glucose level. The subject can self-monitor their progress over period 208 using the current average glucose level and target average glucose level. In some cases, the current average glucose level can be transmitted (periodically or regularly) to a healthcare professional using the physiological parameter analysis system for monitoring and / or analysis.

[0102] Figure 5, with reference to Figure 2, shows an example of a personalized-target mean glucose report that can be generated as output 218 by the physiological parameter analysis system 210 of this disclosure. The illustrative report shown includes a plot of the subject's mean glucose over time (solid line) and a plot of personalized-target mean glucose (shown as a dashed line at 150 mg / dL). Alternatively, other reports may include, but are not limited to, a numerical representation of personalized-target mean glucose along with the subject's mean glucose level over a given time frame (e.g., the last 12 hours), and any combination thereof.

[0103] Personalized target mean glucose levels can be updated over time when the latest relevant physiological parameters, relevant calculations, and / or relevant measurements for one or more of the equations 27-29 are obtained.

[0104] Personalized treatment - patient triage For subjects requiring strict control of glucose levels, an insulin pump can be used in conjunction with a continuous glucose monitor. As illustrated above, the target glucose range is personalized. gly This is based on the following. Therefore, in some cases, subjects with a narrower personalized-target glucose range may be strong candidates for insulin pumps along with continuous glucose monitoring. Triage of subjects who are strong candidates for insulin pumps along with continuous glucose monitoring is based on the width of the personalized-target glucose range and k gly It can be said that this is based on the above.

[0105] The current range between the lower and upper limits of glucose intake is approximately 110 mg / dL. However, as illustrated above, k gly Depending on the circumstances, this range may be narrowed to approximately 60 mg / dL or less. Some embodiments may involve a step of triaging the subject to an insulin pump with continuous glucose monitoring when the personalized-target glucose range falls below a threshold lower than 110 mg / dL.

[0106] Some embodiments include k gly 6.2 * 10 -6 dL * mg -1* day -1 When a higher threshold is exceeded, the patient may be triaged to an insulin pump along with continuous glucose monitoring.

[0107] Some embodiments include k gly The threshold is, for example, 6.2 * 10 -6 dL * mg -1* day -1 When the blood glucose level is lower than this, the subject may be placed in a program to prevent extremely low blood glucose.

[0108] In some embodiments, the step of triaging a subject to an insulin pump with a continuous glucose monitor may be a stepwise triage in which the subject's glucose levels are first continuously monitored for a suitable period (e.g., about 5, 10, 15, 30 days, or longer). This continuous monitoring period can be used to assess whether the subject is capable of substantially managing their glucose levels, or whether an insulin pump is more appropriate or necessary.

[0109] Whether the triage stage proceeds directly to insulin pump with continuous glucose monitoring or is a stepwise triage monitored before treatment using an insulin pump, the indicator (i.e., personalized - broadening of target glucose range, k gly This can be determined by the level of (or any combination thereof). For example, k gly approximately 6.4 * 10 -6 dL * mg -1* day -1Therefore, when the individualized target glucose range is approximately 103 mg / dL, this subject may be more suitable for stepwise triage compared to another subject whose corresponding indicators suggest the use of an insulin pump.

[0110] In some embodiments, triage may be based on a lookup table (for example, one stored in the physiological parameter analysis system of this disclosure). The lookup table may, for example, contain one or more physiological parameters (k gly , k age , and / or K), personalization—broad range of target glucose, and / or correlation of multiple values ​​with each other, including but not limited to other factors described herein such as underlying disease state, family history of disease state, current treatment, age, race, sex, geographical location, type of diabetes, and duration of diabetes diagnosis, and any combination thereof. Columns in the lookup table can, for example, define range or limit values ​​for the parameters described above, and rows can indicate suggestions for action progression, which can be the output 218 of the physiological parameter analysis system 210 in Figure 2. For example, two columns may be k gly Upper and lower bounds can be defined, in which case each row corresponds to an indication of action progression, such as “candidate for insulin pump,” “candidate for closed-loop control system,” “candidate for basal / add-on insulin therapy,” “candidate for basal-only insulin therapy,” or any such treatment used to control diabetes or cause glycation in the subject. In some cases, more than one action progression may be indicated. Therefore, in this example, the subject triage report can easily show indications of action progression.

[0111] Alternatively, the subject triage report may show a map of zones corresponding to the progression of action on a plot defined, for example, by one or more of the parameters described above with respect to a lookup table. In some cases, such zones may be defined by a lookup table labeled with each zone representing a recommendation, and blood glucose parameter points may be shown on the map to indicate the appropriate zone for the subject.

[0112] The two subject triage reports above are examples based on lookup tables, but instead, (1) one or more physiological parameters (k gly , k age It is thought that this can be based on (2) other correlations between the expansion of the personalized-target glucose range and / or other factors described herein and (3) the progress of the action (e.g., mathematical algorithms or matrix analysis).

[0113] As mentioned above, a subject's glycation parameters can help healthcare providers and payers more accurately determine which treatment tool is most appropriate for which subject. For example, while closed-loop insulin pump systems are expensive to use and maintain, subjects with high glycation rates may have a very narrow individualized target glucose range, in which case the safest treatment is to maintain these subjects' glucose levels within that range using a closed-loop insulin pump system.

[0114] In some embodiments, the insulin pump together with the continuous glucose monitor can form a closed-loop system. In some embodiments, the insulin pump together with the continuous glucose monitor can form a mixed-loop system. For example, referring back to Figure 3, the physiological parameter analysis system 310 may further include one or more of its internal components, such as a glucose monitor 324 (e.g., a continuous glucose monitoring system) and one of the aforementioned insulin pumps capable of communicating with the health monitoring device 320.

[0115] Personalized treatment - Titration of diabetes medications In some embodiments, one or more physiological parameters (k) are used to titrate the dose of a diabetes drug (e.g., insulin) to a subject. gly , k age , and K) can be used. For example, referring to Figure 2, the physiological parameter analysis system 210 of this disclosure may determine or have as input (1) one or more physiological parameters, (2) a personalized-target glucose range, (3) a personalized glucose level (e.g., effective plasma glucose level or intracellular glucose level), and / or (4) a personalized-target mean glucose. The physiological parameter analysis system 210 may then output a recommended diabetes medication dose when the glucose level is subsequently measured. An alternative or supplementary output 218 may be a glucose pattern insight report.

[0116] Examples of glucose pattern insight reports can be found in U.S. Patent Application Publication No. 2014 / 0188400 and No. 2014 / 0350369, each of which is incorporated herein by reference. The analyses and reports disclosed in the aforementioned applications are based on one or more physiological parameters (k) of the present disclosure. gly , k age It can be modified based on , and K).

[0117] For example, Figure 6 shows an example of a glucose pattern insight report that can be the output 218 of a physiological parameter analysis system 210 (e.g., an insulin titration system), with reference to Figure 2. The illustrated glucose pattern insight report incorporates an AGP table of blood glucose control measures (or "signal lights"). As shown in the illustration, the report includes an AGP plot over an analysis period (e.g., from about 1 month to about 4 months) showing the personalized-target mean glucose at 120 mg / dL, the mean glucose level for the subject over the analysis period, the glucose level for the subject from the 25th to the 75th percentile over the analysis period, and the glucose level for the subject from the 10th to the 90th percentile over the analysis period. Optionally, the glucose pattern insight report may also display a personalized-target glucose range and / or personalized glucose level (e.g., effective plasma glucose level or intracellular glucose level) compared to the current acceptable glucose range. In addition, the glucose pattern insight report may optionally further include one or more of the following: measured HbA1c levels, cHbA1c levels, adjusted HbA1c levels based on either tested HbA1c or glucose data, and the data range over which mean glucose and associated percentiles are determined.

[0118] Below the AGP plot in the glucose pattern insights report is a table correlating one or more (shown as three) glycemic control measures with the subject's mean glucose level over a given shortened period on each day during the analysis period. This correlation displays a signal light (e.g., green (good), yellow (moderate), or high (red)) corresponding to the pathological risk based on the glycemic control measure. Examples of glycemic control measures include, but are not limited to, the likelihood of low glucose, the likelihood of high glucose, the proximity of mean glucose to the personalized-target mean glucose, the degree of adherence to the personalized-target glucose range and / or personalized glucose level compared to the current tolerable glucose range, the degree of change in mean glucose that is less than (or greater than) the personalized-target mean glucose, and the degree of change in glucose level that is outside (or greater than) the personalized-target glucose range and / or personalized glucose level compared to the current tolerable glucose range.

[0119] In some embodiments, glucose pattern insight reporting can be used as part of an antidiabetic drug titration system, in which case indicator lights (or associated values) can drive a logic unit to provide therapeutic modifications, such as changing the basal dose of antidiabetic drug or the additional amount of antidiabetic drug in relation to meals. For example, when used in conjunction with an automated or semi-automated system for titration, these indicator lights driving the logic unit can provide the subject with titration recommendations.

[0120] Relevant analyses incorporating glucose pattern insight reports and the use of dynamical models described herein can provide more appropriate treatment for subjects with diabetes. In this example, as described above, 5.1 * 10 -6 dL * mg -1* day -1 k glyA subject having [the relevant condition] may have an individualized - target glucose range from about 90 ± 8 mg / dL to about 250 ± 32 mg / dL. This subject is more sensitive to lower glucose levels and may experience fatigue, hunger, dizziness, etc. more frequently when using the currently treated glucose range (70 mg / dL and 180 mg / dL). The analytical logic part used in the glucose pattern insight report described herein that uses one or more physiological parameters (k gly , k age , and K) can include a set value that defines the hypoglycemia risk as a signal light for "possibility of low glucose". For example, when the possibility of low glucose indicates a low risk (e.g., green signal light), it is considered safe to increase the insulin dosage. When the possibility of low glucose indicates a medium risk (e.g., yellow signal light), it is considered that the current risk is within the acceptable range, but no further increase in insulin should be made. Finally, when the possibility of low glucose indicates a high risk, it is recommended to reduce the insulin dosage to return the glucose to an acceptable level. In subjects with a high hypoglycemia risk due to a high lower glucose level threshold, the amount of risk associated with medium and high risks (how much the lower glucose level threshold is exceeded) may be lower than that of subjects with a normal lower glucose level threshold.

[0121] In the above example, the glucose pattern insight report was discussed as output 218, but in other embodiments, other outputs using the same logic and analysis can be used. For example, output 218 can be a value for dosage recommendation.

[0122] One or more physiological parameters (k gly , k ageand K) and related analysis results (e.g., personalized-target glucose range, personalized glucose level, personalized-target average glucose, cHbA1c, and aHbA1c, etc.) can be updated periodically (e.g., every about 3 months to every year). The frequency of update may depend, inter alia, on the subject's glucose level and diabetes history (e.g., how well the subject stays within the specified thresholds), and other morbidities, etc.

[0123] The insulin titration system can optionally utilize errors associated with one or more physiological parameters (k gly k age and K). The error values can be determined by those skilled in the art using standard statistical techniques and can be used as another set of parameters for including the titration system. For example, the titration system can use a low risk amount for hypoglycemia when the lower glucose level of a personalized-target glucose range of about 75 mg / dL has an error of about 7% or less (i.e., a small tolerance lower than the lower glucose level threshold for indicating moderate and high risks can be implemented).

[0124] The dosage of the diabetes medicine (e.g., by titration) can be updated over time when one or more physiological parameters are recalculated.

[0125] Closed-loop and hybrid closed-loop control systems Closed-loop systems and hybrid closed-loop systems that recommend or administer insulin doses to a subject have been developed for insulin delivery based on near real-time glucose readings. These systems are often based on models that represent the subject's physiology, the kinetics of the glucose sensor, and the error characteristics of the glucose sensor. In some embodiments, in order to better meet the needs of the subject, similar to what was described above for insulin titration, one or more physiological parameters (k gly k ageand K) and related analysis results (e.g., personalized - target glucose range, personalized glucose level, personalized - target average glucose, cHbA1c, and aHbA1c, etc.) can be incorporated into the closed - loop system.

[0126] In many cases, the closed - loop system is configured to “drive” the subject's glucose level towards a target range and / or a single glucose target that can be a personalized - target glucose range, a personalized glucose level, and / or a personalized - target average glucose compared to the acceptable target glucose range described herein. For example, for a subject with a high k gly and a high glucose lower limit value for the personalized - target glucose range, the controller can drive the subject's glucose level to remain above the glucose lower limit value based on k gly to avoid lower glucose levels that have a significantly more adverse effect on these subjects than on subjects with a normal glucose range. Similarly, a subject with a low glucose upper limit value for the personalized - target glucose range can have their glucose driven to remain below the personalized glucose upper limit value by the controller of the closed - loop insulin delivery system and the hybrid closed - loop insulin delivery system to reduce the hyperglycemic effect.

[0127] The metrics that the closed - loop insulin delivery system and the hybrid closed - loop insulin delivery system rely on when determining the insulin dosage can be updated over time when recalculating one or more physiological parameters. For example, when recalculating one or more physiological parameters, the personalized - target glucose range, the personalized glucose level, and / or the personalized - target average glucose can be updated.

[0128] Personalized treatment - glycation drugs Diabetes mellitus is a disease caused by the inability of a subject's pancreas to produce sufficient insulin (or any insulin). However, in some cases, the subject's glycation process may be the cause of the body's inability to properly regulate intracellular glucose. Such subjects may respond well to treatment using anti-glycation agents rather than conventional diabetes treatments. The dynamics model of this disclosure is k gly and / or K(k gly This derives (partially based on) the following: Therefore, one or both of these physiological parameters can be used to identify, treat, and / or monitor subjects with glycation disorders.

[0129] Some embodiments involve the use of a glycation agent on a subject. gly and / or monitor K, and optionally K gly The procedure may include a step of changing the drug dosage based on and / or changes in K.

[0130] In some embodiments, the output 218 of the physiological parameter analysis system 210 in Figure 2 is the k calculated by the physiological parameter analysis system 210. gly This can be a glycation agent report including recommendations for glycation agents and / or dosages based on K. This output 218 can be displayed to subjects and / or healthcare providers, etc., to review and adjust glycation agents and / or dosages.

[0131] Alternatively, these dosage recommendations provide the following dosages to be administered to the subject and / or automated drug delivery system. In this case, the system induces the titration of the drug, and the subject can start with the minimum dose or the recommended initial dose. The initial dose is determined based on the subject's current condition and the subject's k gly1 and / or K1, and other factors described herein may be determined. After a sufficient amount of time has elapsed to accurately determine the effect of the current drug dose, k may be determined based on the new measured HbA1c level and the glucose level measured during drug administration. gly2 And / or K2 can be determined. Then, kgly2 and / or K2 (1)k gly1 and / or K1, and / or (2) target k gly And / or it can be determined whether the dosage needs to be changed in comparison to target K. For example, if a subject with a high glycation constitution who is taking a drug intends to reduce the rate of glycation, gly2 If the value remains higher than the desired value, the recommended dosage can be increased according to (1) a standard titration protocol and / or (2) a system (known as a control theory) that addresses how past dosage changes have affected the subject. In another example, the subject's k gly2 If the value is low, the dosage can be reduced. It is thought that the drug can also be titrated to affect K or other parameters. In addition, it is thought that a similar process can be used to recommend non-pharmacological treatments such as blood transfusion or blood collection by inducing that an appropriate amount of blood is affected.

[0132] To monitor and titrate the effects of the glycation agent, k gly The use of and / or K is beneficial to healthcare providers in treating subjects with abnormal glycation physiology.

[0133] The metrics used to determine the dosage of glycation agents can be updated over time by recalculating one or more physiological parameters.

[0134] Identification of abnormal or pathological physiological conditions Dynamic modeling, in certain embodiments, involves physiological parameters for different time periods (e.g., k gly , k age (or k gen k) is given, and / or K), in which case the same parameter is compared over different periods to indicate an abnormal or pathological physiological condition in the subject. gly , k age Changes in k and / or K can indicate an abnormal or pathological condition in the subject. That is, k gly , k age, and / or K differ among subjects, but k for a single individual gly , k age , and / or the change in K is small and slow. Therefore, the change in K over two or three different periods is small. gly , k age The comparison of , and / or K provides information about the subject's physiological condition. For example, k gly , k age When clinically significant changes in and / or K are observed over time, there may be, and are likely to be, an abnormal or pathological physiological condition.

[0135] For example, k gly When a clinically significant change occurs over time, such a clinically significant change may indicate a change in significant glucose carrier levels or cell membranes. Such biological changes may indicate underlying metabolic changes in the subject's body resulting from the physiology of the subject experiencing the disease condition.

[0136] k age and / or k gen When a clinically significant change occurs over time, such a clinically significant change can indicate a change in the subject's immune system, because the immune system is designed to recognize cells that need to be eliminated.

[0137] k age and / or k gen Clinically significant changes in k can be linked, in addition to or instead to the oxygen sensing mechanism in the body, which increases over time. age and / or k gen This can indicate that the subject's body needs more red blood cells to carry more oxygen, or that the oxygen sensing mechanism is not functioning correctly, both of which indicate a change in physiological condition, such as blood loss or a disease state.

[0138] In yet another example (either in combination with the above example or instead), k age and / or k genClinically significant changes in k can be linked to changes in the bone marrow. For example, if the bone marrow suddenly produces more oxygen-carrying red blood cells, the subject's body will respond by destroying or removing more red blood cells. age and / or k gen A clinically significant increase in this can be associated with bone marrow abnormalities.

[0139] In another example, hormonal disorders are k age , k gen , and may result in clinically significant changes in K. Hormones can affect heart rate, contractile strength, blood volume, blood pressure, and erythropoiesis. Stress hormones such as catecholamines and cortisol stimulate the release of reticulocytes from the bone marrow and may also increase erythropoiesis. Therefore, large fluctuations in hormone levels may lead to K age and / or k gen It is possible to change K as a result of changing [something].

[0140] In yet another example, k gly , k age A deviation of K from normal, and / or a deviation of K from normal, can be an indicator of diabetes or prediabetes. gly , k age Using , and / or K may be more effective than standard fasting glucose testing and measured HbA1c. For example, subjects with measured HbA1c within the normal range and normal fasting glucose may use lower k for high glucose levels at non-fasting times. gly This may be the case. Therefore, this subject may be a candidate for early involvement in diabetes that might otherwise go unnoticed based on standard diabetes diagnostic methods.

[0141] In another example, standard diabetes treatment can be used to reduce the HbA1c levels of subjects who have newly elevated measured HbA1c levels. However, k glyThe determination that this is abnormal indicates that the problem is related to glycation physiology rather than the subject's pancreas, which may suggest other forms of more targeted treatment.

[0142] Embodiments of this disclosure are determined k gly , k age , and / or K, including a step indicating changes in these over time and / or possible abnormal or pathological physiological conditions.

[0143] Embodiments of this disclosure provide physiological parameter analysis as a tool for displaying abnormal or pathological conditions of a subject in the manner described herein, and for analyzing and / or monitoring one or more parameters or characteristics relating to the subject's personalized diabetes management.

[0144] Identification of nutritional supplements and / or drugs Some nutritional supplements and drugs interact with the dynamics of glycation, removal, and development of red blood cell hemoglobin in the body. For example, nutritional supplements and drugs used by athletes for doping include, but are not limited to, human growth hormone, nutritional supplements and drugs that increase metabolic levels, and similar substances. Human growth hormone increases the total number of red blood cells, and as a result, k age It can increase. In another example, nutritional supplements and drugs that increase metabolic levels (e.g., exercise mimics such as AMPK agonists) can increase k gly This can affect the following: Therefore, some embodiments involve one or more physiological parameters (k gly , k age , and / or K) can be used as indicators of doping.

[0145] In the first example, one or more physiological parameters (k) that are outside the normal range are considered to be outside the normal range. gly , k age Having , and / or K) can, in some cases, be used as an indicator of doping.

[0146] In another example, in a state where one or more physiological parameters (k gly , k age , and / or K) are determined, continuous monitoring over a period of 10 days or longer may be able to identify a sudden change in a physiological parameter that is considered likely to indicate doping. This can be used either alone or in combination with the above examples where one or more physiological parameters are outside the normal range.

[0147] Physiological age Due to aging, the physiological parameter k age changes, and as a result, K changes. Therefore, k age and / or K (assuming a stable or known change in k gly ) can be used as biomarkers to calculate the standard metabolic age. Generally, over time, k age decreases and K increases. Using the correlation between k age and / or K and age in a healthy body, the metabolic age of a new subject can be calculated. Then, this metabolic age can be used as an indicator of the risk of a new subject for age-related variable conditions such as heart disease, Alzheimer's disease, or osteoporosis. The risk for age-related variable conditions can be used in combination with the family history of age-related variable conditions for preliminary screening and / or preventive treatment. For example, a 54-year-old subject with a metabolic age of 65 and a family history of cardiovascular disease developing in the later stages of life can be examined more frequently for signs and / or progression of cardiovascular disease than a 54-year-old subject with a metabolic age of 50 and a similar family history.

[0148] Specimen monitor and monitoring system Generally, embodiments of the present disclosure are used in conjunction with or as systems, devices, and methods for measuring glucose and optionally at least one other specimen in body fluids. Embodiments described herein can be used to monitor and / or process information regarding glucose and optionally at least one other specimen. Other specimens that can be monitored include, but are not limited to, glucose derivatives HbA1c, total reticulocyte count, RBC GLUT1 levels, acetylcholine, amylase, bilirubin, cholesterol, chorionic gonadotropins, creatine kinase (e.g., CK-MB), creatine, creatinine, DNA, fructosamine, glutamine, growth hormone, hormones, ketones, ketone bodies, lactates, peroxides, prostate-specific antigen, prothrombin, RNA, thyroid-stimulating hormone, and troponins. For example, concentrations of drugs such as antibiotics (e.g., gentamicin, van and comycin), digitoxin, digoxin, stimulant drugs, theophylline, and warfarin can be monitored. In embodiments where glucose and one or more samples are monitored, each sample can be monitored at the same or different times.

[0149] Sample monitors and / or sample monitoring systems (collectively referred to herein as sample monitoring systems) used in conjunction with or as such with systems, devices, and methods for measuring glucose and optionally one or more samples in body fluids may be in vivo sample monitoring systems or in vitro sample monitoring systems. In some cases, the systems, devices, and methods of this disclosure may be used with both in vivo and in vitro sample monitoring systems.

[0150] An in vivo sample monitoring system includes a sample monitoring system that can position or be able to position at least a portion of a sample sensor on a subject's body to obtain information about at least one sample from the body. The in vivo sample monitoring system can be operated without requiring factory calibration. Examples of in vivo sample monitoring systems include, but are not limited to, continuous sample monitoring systems and intermittent sample monitoring systems.

[0151] For example, a continuous sample monitoring system (e.g., a continuous glucose monitoring system) is an in vivo system that can repeatedly or continuously transmit data from a sensor control device to a reader device without prompting (e.g., automatically according to a schedule).

[0152] For example, a sample intermittent monitoring system (or intermittent glucose monitoring system or simply an intermittent system) is an in vivo system that can transmit data from a sensor control device to a reader device as needed, either by scanning with a reader device using a near-field communication (NFC) or radio frequency identification (RFID) protocol.

[0153] An in vivo sample monitoring system may include sensors that, while placed in a living body, come into contact with the subject's bodily fluids and sense the level of one or more samples contained within those fluids. The sensors may be part of a sensor control device located on the subject's body, which includes electronic equipment and a power supply that enable and control the sensing of the samples. Sensor control devices and variations thereof may also be referred to as "sensor control units," "on-body electronic devices" devices or "on-body electronic devices" units, "on-body" devices or "on-body" units, or "sensor data communication" devices or "sensor data communication" units, etc. As used herein, these terms are not limited to devices having sample sensors and encompass devices having other types of sensors, whether for biometric or non-biometric measurements. The term "on-body" means any device that is directly on the body or located in close proximity to the body, such as a wearable device (e.g., eyeglasses, a watch, a wristband or armband, a neckband or necklace).

[0154] An in vivo sample monitoring system may further include one or more reader devices that receive sensed sample data from a sensor control device. These reader devices can process the sensed sample data and / or display it to the subject in any number of formats. These devices and their variations may be referred to as “handheld reader devices,” “reader devices” (or simply “readers”), “handheld electronic devices” (or handheld), “portable data processing” devices or “portable data processing” units, “data receivers,” “receivers” devices or “receivers” units (or simply receivers), “relay” devices or “relay” units, or “remote” devices or “remote” units, etc. Other devices, such as personal computers, may also be used in conjunction with or incorporated into in vivo and in vivo monitoring systems.

[0155] For example, referring to Figure 3, the sensor or part thereof of the in vivo sample monitoring system can be a glucose monitor 324, and the reader device can be a health monitoring device 320. In an alternative embodiment, the entire in vivo sample monitoring system can consist of a health monitoring device 320, a glucose monitor 324 that transmits data to a data network 322, a data processing terminal / PC 3, and / or a server / cloud 328.

[0156] In an in vivo sample monitoring system, one or more physiological parameters (e.g., k) are monitored. gly , k age (or k gen The determination of one or more physiological parameters (e.g., k), and / or K), and / or other analytical results described herein can, in some cases, be performed within an in vivo sample monitoring system. For example, only physiological parameters can be determined within the in vivo sample monitoring system and transmitted to other suitable components of a physiological parameter analysis system that can perform other analyses described herein. In some embodiments, the in vivo sample monitoring system can generate only an output signal corresponding to the glucose level received by another component of the physiological parameter analysis system. In such cases, one or more of the other components of the physiological parameter analysis system can determine one or more physiological parameters (e.g., k), and / or K), and / or other physiological parameters (e.g., k), and / or K gly , k age (or k gen Determine ), and / or K), and optionally perform one or more of the other analyses described herein.

[0157] Figure 7 shows an example of an in vivo sample monitoring system 760. In embodiments of this disclosure, this exemplary in vivo sample monitoring system 760 monitors glucose and optionally one or more other samples.

[0158] The in vivo sample monitoring system 760 includes a sensor control device 762 (which may be at least a part of the glucose monitor 324 shown in Figure 3) and a reader device 764 (which may be at least a part of the health monitoring device 320 shown in Figure 3) that communicate with each other via a local communication path (or communication link) 766 which may be wired or wireless and unidirectional or bidirectional. In the wireless embodiment of the path 766, it may be a communication protocol existing as of the date of this filing or a later developed variation thereof, such as a Near Field Communication (NFC) protocol, RFID protocol, BLUETOOTH® or BLUETOOTH® Low Energy protocol, WiFi protocol, or proprietary protocol.

[0159] The reader device 764 (e.g., a dedicated reader, a cellular phone, or an application-running PDA) also has the capability to communicate via wired, wireless, or a combination thereof with a computer system 768 (which may be at least part of the data processing terminal / PC 326 in Figure 3) on a communication path (or communication link) 770 and with a network 772 (which may be at least part of the data network 322 and / or server / cloud 328 in Figure 3) on a communication path (or communication link) 774, such as the Internet or a cloud. Communication with network 772 may involve communication with a highly reliable computer system 776 located within network 772, or communication with computer system 768 via network 772 through the communication link (or communication path) 778. Communication paths 770, 774, and 778 may be wireless, wired, or both; they may be unidirectional or bidirectional; and they may be part of a telecommunications network such as a Wi-Fi network, a local area network (LAN), a wide area network (WAN), the Internet, or other data network. In some cases, communication paths 770 and 774 can be the same path. All communications through paths 766, 770, and 774 can be encrypted, and each of the sensor control device 762, reader device 764, computer system 768, and high-reliability computer system 776 can be configured to encrypt and decrypt these transmission and reception communications.

[0160] Variations of devices 762 and 764, as well as other components of in vivo-based specimen monitoring systems suitable for use in combination with the embodiments of systems, devices, and methods described herein, are described in U.S. Patent Application Publication No. 2011 / 0213225 (Publication 225), which is incorporated herein by reference in its entirety for all purposes.

[0161] The sensor control device 762 may include a housing 780 that encloses an in vivo sample monitoring circuit and a power supply. In this embodiment, the in vivo sample monitoring circuit is electrically coupled to a sample sensor 782 that extends through an adhesive patch 784 and protrudes away from the housing 780. The adhesive patch 784 contains an adhesive layer (not shown) for adhesion to the skin surface of the subject's body. Other forms of body adhesion to the body may be used in addition to or instead of the adhesive.

[0162] The sensor 782 is designed to be at least partially inserted into the subject's body, in which case the sensor 782 can be in fluid contact with the subject's bodily fluids (e.g., subcutaneous (subdermal) fluid, dermal fluid, or blood) and can be used in conjunction with an in vivo sample monitoring circuit to measure the subject's sample-related data. The sensor 782 and any attached sensor control electronics can be attached to the body in any desirable manner. For example, using an insertion device (not shown), all or part of the sample sensor 782 can be positioned to penetrate the outer surface of the subject's skin and be in contact with the subject's bodily fluids. In this case, the insertion device can position the sensor control device 762 on the skin using an adhesive patch 784. In other embodiments, the insertion device can first position the sensor 782, and then the attached sensor control electronics can be coupled to the sensor 782 manually or using a mechanical device. Examples of insertable devices are described in U.S. Patent Publication Nos. 2008 / 0009692, 2011 / 0319729, 2015 / 0018639, 2015 / 0025345, and 2015 / 0173661, the entire contents of all these documents incorporated herein by reference for all purposes.

[0163] After collecting raw data from the subject's body, the sensor control device 762 can apply analog signal conditioning to the data to convert it into conditioned raw data in digital form. In some embodiments, this conditioned raw data can be encoded for transmission to another device (e.g., a reader device 764), which then algorithmically processes this digital raw data into a final form representing the subject's measured biometrics (e.g., a form that can be easily processed for display to the subject, or a form that can be easily used in the analysis module 320B in Figure 3). This algorithmically processed data can then be formatted or graphically processed for digital display to the subject. In other embodiments, the sensor control device 762 algorithmically processes the digital raw data into a final form representing the subject's measured biometrics (e.g., sample level), then encodes this data and can wirelessly transmit it to the reader device 764, which can then format or graphically process the received data for digital display to the subject. In other embodiments, the sensor control device 762 graphically processes the data in its final form to await display, and this data can be displayed on the sensor control device 762's display or transmitted to the reader device 764. In some embodiments, the final form of biometric data (before graphical processing) is used by the system without further processing for display to the subject (e.g., incorporated into a diabetes monitoring regime). In some embodiments, the sensor control device 762 and the reader device 764 transmit the raw digital data to another computer system for algorithmic processing and display.

[0164] The reader device 764 may include a display 786 for outputting information to a subject (e.g., one or more physiological parameters or outputs such as cHbA1c derived therefrom) and / or for receiving input from the subject, and an optional input component 788 (or more) such as a button, actuator, touch-sensitive switch, capacitive switch, pressure-sensitive switch, or jog wheel for inputting data, commands, or otherwise controlling the operation of the reader device 764. In certain embodiments, the display 786 and the input component 788 may be integrated into a single component, for example, in which case the display may measure the presence and location of physical touch on the display, such as a touchscreen subject interface (which may be at least a part of the subject interface 320A in Figure 3). In certain embodiments, the input component 788 of the reader device 764 may include a microphone so that the function and operation of the reader device 764 can be controlled by voice commands, and the reader device 764 may include software configured to analyze audio input received from the microphone. In certain embodiments, the output components of the reader device 764 include a speaker (not shown) for outputting information as an audible signal. The sensor control device 762 may include a speaker, a similar voice-enabled component such as a microphone, and software routines for generating, processing, and storing voice-driven signals.

[0165] The reader device 764 may also include one or more data communication ports 790 for wired data communication with an external device such as a computer system 768. Exemplary data communication ports 790 include, but are not limited to, USB ports, mini USB ports, USB Type-C ports, USB Micro-A ports and / or USB Micro-B ports, RS-232 ports, Ethernet ports, FireLine ports, or other similar data communication ports configured to connect to a suitable data cable. The reader device 764 may further include an integrated or attachable in vitro glucose meter, which includes an in vitro test strip port (not shown) for receiving an in vitro test strip to perform in vitro blood glucose measurements.

[0166] The reader device 764 can display measured biometric data wirelessly received from the sensor control device 762 and can be configured to output alarms (e.g., visual alarms, auditory alarms, or any combination thereof) that can be visual, audible, tactile, or any combination thereof, warning notifications, glucose levels, etc. Further details and other display embodiments can be found, for example, in U.S. Patent Application Publication No. 2011 / 0193704, the entirety of which is incorporated herein by reference for all purposes.

[0167] The reader device 764 can function as a data conduit for transmitting measurement data from the sensor control device 762 to the computer system 768 or the high-reliability computer system 776. In certain embodiments, data received from the sensor control device 762 can be stored (permanently or temporarily) in one or more memories of the reader device 764 before being uploaded to the computer system 768, the high-reliability computer system 776, or the network 772.

[0168] The computer system 768 may be a personal computer, server terminal, laptop computer, tablet, or other suitable data processing device. The computer system 768 may be (or include) software for data management and analysis, and for communication with components within the specimen monitoring system 760. The computer system 768 may be used by a subject, healthcare professional, or other user to display and / or analyze biometric data measured by the sensor control device 762. In some embodiments, the sensor control device 762 may communicate biometric data directly to the computer system 768 without using a relay such as the reader device 764, or indirectly using an internet connection (also optionally without first sending to the reader device 764). The operation and use of the computer system 776 are described in more detail in Publication 225 incorporated herein. The specimen monitoring system 760 may also be configured to operate with a data processing module (not shown), as described in Publication 225, also incorporated herein.

[0169] The highly reliable computer system 776 may be owned by the manufacturer or distributor of the sensor control device 762 through a secure physical or virtual connection and may be used as a server to perform authentication of the sensor control device 762 for secure storage of the subject's biometric data and / or to function as a data analysis program (e.g., accessible via a web browser) for performing analysis on the subject's measurement data.

[0170] In vivo sample monitoring systems can be used in conjunction with or as part of an integrated diabetes management system. For example, an integrated diabetes management system may include an in vivo sample monitoring system and a nutritional supplement / drug delivery system, more specifically an in vivo glucose monitoring system and an insulin delivery system (e.g., an insulin pump). An integrated diabetes management system can be closed-loop, open-loop, or a hybrid of these. A closed-loop system provides complete control over sample monitoring time and the dosage and timing of nutritional supplement / drug administration. An open-loop system allows the subject to have complete control over sample monitoring time and the dosage and timing of nutritional supplement / drug administration. A hybrid system relies primarily on a closed-loop system configuration but can allow for subject involvement.

[0171] In vitro sample monitoring systems come into contact with bodily fluids outside the body. In some cases, an in vitro sample monitoring system includes a weighing device having a port for receiving a subject's bodily fluids (e.g., on a sample test strip / swab or by collecting bodily fluids) that can be analyzed to determine the subject's sample level.

[0172] Exemplary Embodiments A first non-limiting exemplary embodiment of the present disclosure includes the steps of: measuring a patient's glucose level over time; measuring the HbA1c of individual red blood cells in a sample comprising a plurality of red blood cells; deriving the measured red blood cell HbA1c distribution of the sample; and (a) an erythrocyte removal constant (k age (b) Red blood cell hemoglobin glycation rate constant (k gly The method comprises the steps of: (a) calculating at least one physiological parameter selected from the group consisting of (c) the measured blood cell HbA1c distribution and glucose level over time in the patient; (b) the apparent glycation constant (K); and / or (c) the apparent glycation constant (K). (i) Derive the calculated HbA1c, (ii) Derive corrected HbA1c, (iii) Deriving the personalized target glucose range, the personalized target glucose upper limit, and / or the personalized target glucose lower limit, (iv) Personalization - Deriving the target average glucose, (v) To derive personalized treatment for subject triage, (vi) To derive personalized treatments for the titration of diabetes medications, (vii) To derive a personalized closed-loop or hybrid closed-loop control system, (viii) Developing personalized treatments using glycation drugs, (ix) Identifying abnormal or pathological physiological conditions, (x) Identify any nutritional supplements and / or drugs present during the test. (xi) Identifying physiological age, (xii) Treating a patient and / or adjusting the treatment of a patient based on one or more values ​​and / or ranges derived and / or identified in (i) to (xii), The step may further include using (a), (b), and / or (c) toward one or more of the following:

[0173] A second non-limiting exemplary embodiment of the present disclosure includes a sample sensor configured to measure glucose levels in body fluids, one or more processors, and one or more processors operationally coupled to the one or more processors, causing the one or more processors to receive multiple glucose levels in body fluids from the sample sensor over time when executed by the one or more processors, and to receive the measured blood cell HbA1c distribution, and (a) an erythrocyte removal constant (k age (b) Red blood cell hemoglobin glycation rate constant (k glyThe system includes a monitor device which includes a memory that stores instructions causing at least one physiological parameter selected from the group consisting of (a), (b), and / or (c) apparent glycation constant (K) to be determined based on the measured blood cell HbA1c distribution and glucose level over time. When the instructions are executed by one or more processors, one or more processors will be instructed to determine based on (a), (b), and / or (c), (i) Derive the calculated HbA1c, (ii) Derive corrected HbA1c, (iii) Deriving the personalized target glucose range, the personalized target glucose upper limit, and / or the personalized target glucose lower limit, (iv) Personalization - Deriving the target average glucose, (v) To derive personalized treatment for subject triage, (i) To derive personalized treatments for the titration of diabetes medications, (i) To derive a personalized closed-loop or hybrid closed-loop control system, (viii) Developing personalized treatments using glycation drugs, (ix) Identifying abnormal or pathological physiological conditions, (x) Identify any nutritional supplements and / or drugs present during the test. (xi) Identifying physiological age, and (xii) Treating a patient and / or adjusting the treatment of a patient based on one or more values ​​and / or ranges derived and / or identified in (i) to (xii), They shall implement one or more of the following.

[0174] Another non-limiting exemplary embodiment of the present disclosure includes the steps of: measuring a patient's glucose level over time; measuring the HbA1c of individual red blood cells in a sample comprising multiple red blood cells; deriving the measured red blood cell HbA1c distribution of the sample; and (a) an erythrocyte removal constant (k age ), (b) Erythrocyte glycation rate constant (k glyA method comprising the steps of: calculating at least one physiological parameter selected from the group consisting of (c) a personalized lower limit of glucose, a personalized upper limit of glucose, and a personalized target mean glucose (GT) based on the patient's measured blood cell HbA1c distribution and glucose level over time; and adjusting the glucose level target based on at least one physiological parameter. This non-exclusive exemplary embodiment is characterized by: Element 1: the glucose level target is one or more values ​​selected from the group consisting of a personalized lower limit of glucose, a personalized upper limit of glucose, and a personalized target mean glucose; Element 2: the personalized upper limit of glucose is given by formula 23; Element 3: Element 1 and the personalized lower limit of glucose are given by formula 21; Element 4: Element 1 and at least one physiological parameter comprises K, and when AT is the target HbA1c value, the personalized target mean glucose (GT) is equal to AT / (K(1-AT)); Element 5: the method adjusts the subject based on the glucose level target Element 6: The method further comprises a treatment step, characterized in that the treatment step of Element 5 comprises a step of administering and / or adjusting insulin, glycation drug, exercise regimen, dietary intake, or a combination thereof, Element 7: A plurality of first glucose levels are selected from a group consisting of blood, dermal fluid, interstitial fluid, or a combination thereof and measured in body fluids, Element 8: The method further comprises a step of displaying a glucose level target, Element 9: The method further comprises a step of receiving the subject's glucose level after adjusting the glucose level target and a step of displaying an alarm when the glucose level is outside the glucose level target, Element 10: The method, k age Element 11: The method may further include one or more of the following steps: a step of calculating metabolic age based on and / or K; a step of determining a calculated glycated hemoglobin (cHbA1c) level; or a step of identifying the presence of abnormal or pathological physiological conditions and / or doping indicators based on a comparison of at least one first physiological parameter with at least one second physiological parameter.

[0175] A third non-limiting exemplary embodiment of the present disclosure includes a sample sensor configured to measure glucose levels in body fluids, one or more processors, and one or more processors operationally coupled to the one or more processors, causing the one or more processors to receive multiple glucose levels in body fluids from the sample sensor over time when executed by the one or more processors, and to receive the measured blood cell HbA1c distribution, and (a) an erythrocyte removal constant (k age ), (b) Erythrocyte glycation rate constant (k gly A system for determining a glucose level target, comprising a monitoring device including a memory for storing instructions to adjust the glucose level target based on the measured blood cell HbA1c distribution and glucose level over time, and causing at least one physiological parameter selected from the group consisting of (c) a personalized lower glucose limit, a personalized upper glucose limit, and a personalized target glucose mean value, element 14: at least one physiological parameter is k gly It includes the feature that a personalized glucose upper limit can be calculated using equation 23, element 15: at least one physiological parameter is k gly Element 16: The system further includes the feature that a personalized lower limit of glucose can be calculated using Equation 21, and at least one physiological parameter has K, and the personalized target mean glucose (GT) is given by Equation 26, Equation 27, or Equation 28, Element 17: The system further includes a display, and when an instruction is executed by one or more processors, it causes one or more processors to further display the glucose level target, Element 18: When an instruction is executed by one or more processors, it causes one or more processors to k ageElement 19: The instruction causes one or more processors to further determine metabolic age based on and / or K when executed by one or more processors; Element 20: The instruction causes one or more processors to identify the presence of abnormal or pathological physiological conditions and / or doping indicators based on a comparison of at least one first physiological parameter and at least one second physiological parameter when executed by one or more processors; Element 21: The instruction, when executed, causes one or more processors to determine an insulin dose based on a glucose level target and transmit it to an insulin pump system, and may further include one or more of these features.

[0176] A fourth non-limiting exemplary embodiment of the present disclosure includes the steps of: receiving (and / or measuring) a plurality of first glucose levels relating to a subject over time; receiving (and / or measuring) the HbA1c levels of individual red blood cells in a sample comprising a plurality of red blood cells; deriving a measured red blood cell HbA1c distribution of the sample based on the HbA1c levels of individual red blood cells; and (a) an erythrocyte removal constant (k age ), (b) Erythrocyte glycation rate constant (k glyThe method comprises the steps of: (a) a measured blood cell HbA1c distribution and glucose levels over time in a subject; (b) a measured blood cell HbA1c level and / or (c) an apparent glycation constant (K); (c) a measured blood cell HbA1c level and / or (c) an apparent glycation constant (K); and / or (d) a measured blood cell HbA1c level and / or (c) an apparent glycation constant (K). The step of measuring glucose levels may include the steps of: collecting body fluid from the subject using a sample sensor; and measuring a plurality of first glucose levels using a sample sensor. A fourth non-exclusive exemplary embodiment is an element 25: the method further comprises the steps of: receiving (and / or measuring) a plurality of second glucose levels for a subject over a period of time; and deriving a calculated HbA1c (cHbA1c) level for the subject based on at least one physiological parameter and a plurality of second glucose levels (e.g., using formula 17 or formula 18); element 26: the method further comprises the steps of: diagnosing, treating, and / or monitoring the subject based on the cHbA1c level; and element 27: the method further comprises the steps of: The method is characterized by a step of treating the subject, comprising a step of administering and / or adjusting insulin dosage, glycation drug dosage, exercise regime, dietary intake, or a combination thereof; Element 28: Element 25 and the method further comprising a step of displaying the cHbA1c level (e.g., on system 210, on system 310, on a glucose measuring device, and / or on a closed-loop insulin pump system where multiple first and / or second glucose levels are measured); Element 29: Element 25 and the method further comprising a step of displaying the cHbA1c level and k age The established standard k age (k ref age ) further comprising the step of calculating the adjusted HbA1c (aHbA1c) for the subject based on (for example, using formula 19), element 30: The method comprises the step of receiving (and / or measuring) the laboratory measured HbA1c level for the subject and the laboratory measured HbA1c level and k age The established standard k age (k ref ageThe method further comprises the steps of calculating the adjusted HbA1c (aHbA1c) level for the subject based on (for example, using formula 19), element 31: element 25 and the cHbA1c level and a defined standard K(K ref ) further comprising the step of calculating the adjusted HbA1c (aHbA1c) level based on (for example, using formula 20), element 32: The method comprises the step of receiving (and / or measuring) the laboratory measured HbA1c level for a subject and the laboratory measured HbA1c level and a defined standard K(K refElement 33: Element 29, Element 30, Element 31, or Element 32, and further comprising a step of diagnosing, treating and / or monitoring a subject based on aHbA1c levels, Element 34: Element 33, and a step of treating the subject comprising administering and / or adjusting insulin dosage, glycation drug dosage, exercise regimen, dietary intake, or a combination thereof, Element 35: Element 29, Element 3 0, element 31, or element 32, and the method further comprises the step of displaying cHbA1c levels and / or aHbA1c levels (e.g., on system 210, on system 310, on a glucose measuring device, and / or on a closed-loop insulin pump system where multiple first and / or second glucose levels were measured), element 36: element 29, element 30, element 31, or element 32, and the method further comprises the step of deriving a personalized target glucose range (e.g., using equations 22 and 24), deriving a personalized upper glucose limit Element 37: Element 36 and the method further comprises a step of deriving a step and / or a personalized lower glucose limit (for example, using Equation 24, based on aHbA1c level and laboratory measured HbA1c) (for example, using Equation 22), and a step of diagnosing, treating and / or monitoring a subject based on a personalized target glucose range, a personalized upper glucose limit and / or a personalized lower glucose limit, Element 38: Element 37, and a step of treating the subject, including insulin dosage, glycation drug dosage, exercise regimen , characterized by comprising a step of administering and / or adjusting dietary intake or a combination thereof, Element 39: Element 36 and the method further comprising a step of displaying a personalized-target glucose range, a personalized upper glucose limit, and / or a personalized lower glucose limit (for example, on system 210, on system 310, on a glucose measuring device, and / or on a closed-loop insulin pump system where multiple first and / or second glucose levels were measured), Element 40: Element 36 and the method further comprising a step of personalizing the target glucose range,The method further comprises the steps of receiving the subject's glucose level after deriving a personalized upper glucose limit and / or a personalized lower glucose limit, and displaying an alert (visually, audibly, and / or tactilely (related to touch)) when the glucose level exceeds the personalized upper glucose limit and / or falls below the personalized lower glucose limit, which are outside the personalized-target glucose range, Element 41: Element 29, Element 30, Element 31, or Element 32, and the Method for deriving a personalized-target mean glucose Element 42: The method further comprises a step of diagnosing, treating, and / or monitoring a subject based on personalized-target mean glucose (for example, using formula 26, formula 27, or formula 28); Element 43: The method is characterized in that the step of treating the subject is performed and comprises a step of administering and / or adjusting insulin dosage, glycation drug dosage, exercise regimen, dietary intake, or a combination thereof; Element 44: The method displays personalized-target mean glucose (for example, on system 210, etc.) The method further comprises steps such as on stem 310, on a glucose measuring device, and / or on a closed-loop insulin pump system where multiple first and / or second glucose levels are measured, element 45: element 29, element 30, element 31, or element 32, and the step of deriving a personalized treatment toward subject triage based at least partially on aHbA1c levels, a step of deriving a personalized treatment toward the titration of diabetes drugs, a step of deriving a personalized closed-loop or hybrid closed-loop control system, and a step of using glycation drugs The method further includes one or more of the following steps: deriving a prescribed treatment; identifying abnormal or pathological physiological conditions; identifying nutritional supplements and / or drugs present during the test; and identifying physiological age; Element 46: Element 25 and the Method further include the steps of: deriving a personalized treatment toward subject triage based at least partially on cHbA1c levels; deriving a personalized treatment toward the titration of diabetes drugs; deriving a personalized closed-loop or hybrid closed-loop control system; deriving a personalized treatment using glycation agents;The method further includes one or more of the following steps: identifying abnormal or pathological physiological conditions, identifying nutritional supplements and / or drugs present during the test, and identifying physiological age; Element 47: The method, k, gly The established standard k gly (k ref gly Element 48: The method further comprises a step of deriving a personalized target glucose range based on the personalized target glucose range, a personalized upper glucose limit, and / or a personalized lower glucose limit (for example, using Equations 21 and 23), a step of deriving a personalized upper glucose limit (for example, using Equation 23), and / or a step of deriving a personalized lower glucose limit (for example, using Equation 21), Element 47 and the method further comprises a step of diagnosing, treating and / or monitoring a subject based on the personalized target glucose range, a personalized upper glucose limit, and / or a personalized lower glucose limit, Element 49: The step of treating the subject is carried out and comprises a step of administering and / or adjusting insulin dosage, glycation drug dosage, exercise regime, dietary intake, or a combination thereof, Element 50: The method further comprises a step of deriving a personalized target glucose range, a personalized glucose Element 51: Element 47, further comprising a step of displaying the upper limit and / or personalized lower limit of glucose (for example, on system 210, on system 310, on a glucose measuring device, and / or on a closed-loop insulin pump system where multiple first and / or second glucose levels were measured), and the method further comprising a step of receiving a glucose level for a subject after deriving a personalized-target glucose range, a personalized upper limit of glucose, and / or a personalized lower limit, and displaying an alarm (visually, audibly, and / or tactilely (related to touch)) when the glucose level is outside the personalized-target glucose range, above the personalized upper limit of glucose, and / or below the personalized lower limit, Element 52: The method, k gly The established standard k gly (k ref glyElement 53: Element 52 and the method further comprises a step of deriving a personalized glucose level based on the measured glucose level (e.g., using formula 25 or formula 26), Element 53: Element 52 and the method further comprises a step of diagnosing, treating and / or monitoring a subject based on the personalized glucose level (e.g., a personalized lower glucose limit compared to the current tolerable glucose range or intracellular glucose level compared to the current tolerable intracellular glucose level range (i.e., LIGL~UIGL)), Element 54: Element 53 and the step of treating the subject is performed, such as insulin dosage, glycation drug dosage, exercise regimen, dietary intake, or a combination thereof. Element 55: The method may further include one or more of the following features: a step of administering and / or adjusting; a step of displaying a personalized glucose level (e.g., on system 310, on system 410, on a glucose measuring device, and / or on a closed-loop insulin pump system where multiple first and / or second glucose levels were measured); and a step of displaying an alert (visually, audibly, and / or tactilely (related to touch)) when the personalized glucose level is outside the current respective acceptable glucose range.

[0177] A fifth non-exclusive exemplary embodiment of the present disclosure is a sample sensor configured to measure glucose levels in a body fluid, one or more processors, and a monitor device operationally coupled to the one or more processors and including a memory that stores instructions causing the sample sensor (or a larger system in which the sample sensor constitutes part) to optionally perform the method of the fourth non-exclusive exemplary embodiment, which includes one or more of elements 25 to 56, when executed by the one or more processors.

[0178] A sixth non-limiting exemplary embodiment of the present disclosure is a closed-loop insulin pump system comprising a sample sensor configured to measure glucose levels in a body fluid, an insulin pump, one or more processors, and a monitor device operationally coupled to the one or more processors and including a memory that stores instructions causing the system to perform the method of the fourth non-limiting exemplary embodiment (optionally including one or more of elements 25 to 56) when executed by the one or more processors, wherein when a treatment is administered, the treatment includes the step of administering an insulin dose through the closed-loop insulin pump system.

[0179] A seventh non-limiting exemplary embodiment uses a model that considers membrane-transmitting glucose transport and glycation to determine the erythrocyte glycation rate constant (k) based on (1) a plurality of first glucose levels and (2) the HbA1c levels of individual erythrocytes in a sample comprising a plurality of erythrocytes. gly ), erythropoiesis rate constant (k gen ), red blood cell removal constant (k age The method comprises the steps of: determining at least one physiological parameter relating to a subject selected from the group consisting of (i) and apparent glycation constant (K); receiving (and / or measuring) a plurality of second glucose levels relating to the subject over a period of time; and deriving a calculated HbA1c (cHbA1c) level relating to the subject based on the at least one physiological parameter and the plurality of second glucose levels (for example, using formula 17 or formula 18). Yet another embodiment may further include one or more of elements 26 to 46.

[0180] An eighth non-exclusive exemplary embodiment includes the steps of receiving (and / or measuring) a plurality of first glucose levels for a subject over a first period, receiving (and / or measuring) a first glycated hemoglobin (HbA1c) level for the subject corresponding to the end of the first period, and determining the erythrocyte glycation rate constant (k) based on (1) the plurality of first glucose levels and (2) the first HbA1c level using a model that takes into account membrane trans-glucose transport and glycation. gly), erythropoiesis rate constant (k gen ), red blood cell removal constant (k age The method comprises the steps of: determining at least one physiological parameter relating to a subject selected from the group consisting of (1) the apparent glycation constant (K); receiving (and / or measuring) a plurality of second glucose levels relating to the subject over a second period; and deriving a calculated HbA1c (cHbA1c) level based on the at least one physiological parameter and the plurality of second glucose levels (for example, using formula 17 or formula 18). Yet another embodiment may further include one or more of elements 26 to 46.

[0181] A ninth non-exclusive exemplary embodiment of the present disclosure is a sample sensor configured to measure glucose levels in a body fluid, one or more processors, and a monitor device operationally coupled to the one or more processors and including a memory that stores instructions causing the sample sensor (or a larger system in which the sample sensor constitutes part) to perform the method of the seventh or eighth non-exclusive exemplary embodiment (optionally including one or more of elements 26 to 46) when executed by the one or more processors.

[0182] A tenth non-limiting exemplary embodiment of the present disclosure is a closed-loop insulin pump system comprising a sample sensor configured to measure glucose levels in a body fluid, an insulin pump, one or more processors, and a monitor device operationally coupled to the one or more processors and including a memory that stores instructions causing the system to perform the method of the seventh or eighth non-limiting exemplary embodiment (optionally including one or more of elements 26 to 46) when executed by the one or more processors, wherein when a treatment is administered, the treatment includes the step of administering an insulin dose through the closed-loop insulin pump system.

[0183] An eleventh non-limiting embodiment of the present disclosure includes the steps of receiving (and / or measuring) laboratory-measured HbA1c for a subject and determining the erythrocyte turnover rate (k) for the subject based on (1) a plurality of first glucose levels and (2) the HbA1c levels of individual erythrocytes in a sample comprising a plurality of erythrocytes, using a model that takes into account membrane trans-glucose transport and glycation. age The stage of determining the HbA1c level and k age The established standard k age (k ref age The method comprises the steps of: calculating the adjusted HbA1c (aHbA1c) level for the subject based on (for example, using Equation 19); and

[0184] A twelfth non-limiting exemplary embodiment of the present disclosure comprises the steps of receiving (and / or measuring) a laboratory-measured HbA1c level relating to a subject, and determining the erythrocyte turnover rate (k) relating to the subject based on (1) a plurality of first glucose levels and (2) the HbA1c levels of individual erythrocytes in a sample comprising a plurality of erythrocytes, using a model that takes into account membrane trans-glucose transport and glycation. age The stage of determining the HbA1c level and the established standard K (K ref The method comprises the steps of: calculating the adjusted HbA1c (aHbA1c) level for a subject based on (for example, using equation 20); and

[0185] A thirteenth non-exclusive exemplary embodiment of the present disclosure is a sample sensor configured to measure glucose levels in a body fluid, one or more processors, and a monitor device operationally coupled to the one or more processors and including a memory that stores instructions causing the sample sensor (or a larger system in which the sample sensor is part) to perform the method of the eleventh or twelfth non-exclusive exemplary embodiment (optionally including one or more of elements 33 to 45) when executed by the one or more processors.

[0186] A 14th non-limiting exemplary embodiment of the present disclosure is a closed-loop insulin pump system comprising a sample sensor configured to measure glucose levels in a body fluid, an insulin pump, one or more processors, and a monitor device operationally coupled to the one or more processors and including a memory for storing instructions that, when executed by the one or more processors, cause the system to perform the method of the 11th or 12th non-limiting exemplary embodiment (optionally including one or more of elements 33 to 45), wherein when a treatment is administered, the treatment includes the step of administering an insulin dose through the closed-loop insulin pump system.

[0187] A 15th non-limiting exemplary embodiment of the present disclosure includes the steps of: receiving (and / or measuring) a plurality of first glucose levels over time for a subject; receiving (and / or measuring) the HbA1c levels of individual red blood cells in a sample comprising a plurality of red blood cells; deriving a measured red blood cell HbA1c distribution of the sample based on the HbA1c levels of individual red blood cells; and (a) an erythrocyte removal constant (k age ), (b) Erythrocyte glycation rate constant (k gly The steps include: calculating at least one physiological parameter selected from the group consisting of (c) the apparent glycation constant (K) based on the subject's measured blood cell HbA1c distribution and glucose level over time, and k gly The established standard k gly (k ref glyA method comprising the steps of deriving a personalized glucose level based on a measured glucose level (e.g., using formula 25 or formula 26), wherein the step of measuring the glucose level may involve the steps of collecting body fluid from the subject using a sample sensor and measuring a plurality of first glucose levels using a sample sensor. A 15th non-exclusive exemplary embodiment is element 60: The method further comprises the step of diagnosing, treating and / or monitoring the subject based on a personalized glucose level (e.g., a personalized lower glucose limit compared to a current tolerable glucose range or intracellular glucose level compared to a current tolerable intracellular glucose level range (i.e., LIGL~UIGL)), element 61: The steps of element 60 and treating the subject are carried out and comprise the steps of administering and / or adjusting insulin dosage, glycation drug dosage, exercise regimen, dietary intake, or a combination thereof. Features, Element 62: The method further comprises a step of displaying a personalized glucose level (for example, on system 310, on system 410, on a glucose measuring device, and / or on a closed-loop insulin pump system where multiple first and / or second glucose levels are measured), and Element 63: The method further comprises one or more of the steps of displaying an alert (visually, audibly, and / or tactilely (related to touch)) when the personalized glucose level is outside the current respective acceptable glucose range.

[0188] A sixteenth non-exclusive exemplary embodiment of the present disclosure is a closed-loop insulin pump system comprising a sample sensor configured to measure glucose levels in a body fluid, one or more processors, and a monitor device operationally coupled to the one or more processors and including a memory that stores instructions causing the one or more processors to optionally perform a method of the fifteenth non-exclusive exemplary embodiment, which includes one or more of elements 60 to 63, when executed by the one or more processors.

[0189] A 14th non-limiting exemplary embodiment of the present disclosure is a closed-loop insulin pump system comprising a sample sensor configured to measure glucose levels in a body fluid, an insulin pump, one or more processors, and a monitor device operationally coupled to the one or more processors and including a memory for storing instructions that cause the one or more processors to perform the method of the 15th non-limiting exemplary embodiment (optionally including one or more of elements 60 to 63), wherein when a treatment is administered, the treatment includes the step of administering an insulin dose through the closed-loop insulin pump system.

[0190] Unless otherwise indicated, all figures representing quantities, etc., within this specification and the accompanying claims shall be understood in all cases to be modified by the term “approximately.” Accordingly, unless otherwise indicated, the numerical parameters set forth herein and in the claims are approximations, which may vary depending on the desired characteristics sought by the embodiments of this disclosure. Not with the intention of limiting the application of the principle of equivalents to the claims, but at a minimum, each numerical parameter should be interpreted by applying ordinary rounding techniques, taking into account at least the number of significant figures reported.

[0191] This specification provides one or more exemplary embodiments incorporating various features. For the purposes of clarity, this application does not describe or show all features of the physical implementation. It is understood that in developing a physical embodiment incorporating the embodiments of this disclosure, many implementation-specific decisions must be made, such as compliance with system-related, commercial-related, government-related, and other constraints, which vary from implementation to implementation and change over time, in order to achieve the developer's goals. While the developer's efforts may be time-consuming, such efforts are nevertheless routine for those skilled in the art who are interested in this disclosure.

[0192] In this specification, various systems, tools, and methods are described in terms of "comprising" various components or stages, but systems, tools, and methods can "essentially constitute" or "constitute" various components and stages.

[0193] When used herein, the phrase "at least one of" preceding a set of items in which the terms "and" or "or" separate any of the items modifies the list as a whole, rather than each member of the list (i.e., each item). The phrase "at least one of" allows for meanings that include at least one of any of the items, at least one of any combination of the items, and / or at least one of each of the items. For example, each of "at least one of A, B, and C" or "at least one of A, B, or C" means A only, B only, or C only, any combination of A, B, and C, and / or at least one of each of A, B, and C.

[0194] Accordingly, the systems, tools, and methods of this disclosure are designed to fully achieve the stated objectives and benefits, as well as those inherent therein. The teachings of this disclosure can be modified and implemented in different but equivalent ways that will be apparent to those skilled in the art who benefit from the teachings herein; therefore, the specific embodiments disclosed above are merely illustrative. Furthermore, no limitation is intended to any structural or design details shown herein beyond those described in the claims below. Accordingly, the specific exemplary embodiments disclosed above can be modified, combined, or altered, and it is clear that all such variations are within the scope of this disclosure. The systems, tools, and methods disclosed herein exemplary can be adequately implemented without any elements not specifically disclosed herein and / or any optional elements disclosed herein. While systems, tools, and methods are described in terms of "comprising," "containing," or "incorporating" various components or stages, systems, tools, and methods can "basically constitute" or "constitute" various components and stages. All figures and scopes disclosed above may differ to some extent. When disclosing a numerical range with lower and upper limits, all digits and all inclusions within that range are specifically disclosed. In particular, all value ranges disclosed herein ("from about a to about b," or equivalently "from about a to b," or equivalently "about a to b") should be understood to indicate all digits and ranges included within that broad value range. Similarly, terms in the claims have their obvious and ordinary meanings unless otherwise explicitly and clearly defined by the patentee. Furthermore, non-plural nouns used in the claims mean one or more. In the event of any conflict between the use of a word or term herein and the use of a word or term in one or more patents or other documents that may be incorporated herein by reference, the definition consistent with this specification shall be adopted.

Claims

1. A method performed by a computer, The computer receives a plurality of first glucose levels over a first period relating to the subject, The computer receives the HbA1c level of individual red blood cells in a sample of the subject's blood, which contains multiple red blood cells. The computer receives the blood cell HbA1c distribution of the sample, wherein the blood cell HbA1c distribution of the sample is based on the HbA1c levels of individual red blood cells. The aforementioned computer, (a) Red blood cell removal constant (k age ), (b) Erythrocyte glycation rate constant (k gly ), and / or (c) A step of calculating at least one physiological parameter selected from the group consisting of apparent glycation constants (K), The step of calculating the at least one physiological parameter includes generating the derived individual blood cell HbA1c distribution from a plurality of first glucose levels over the first period relating to the subject, The step of generating the derived individual blood cell HbA1c distribution from a plurality of first glucose levels over the first period relating to the subject is: A step of determining glucose (GI(t)) as a function of time in the subject based on a plurality of first glucose levels over the first period, The steps include converting the glucose (GI(t)) into an intracellular glucose concentration (GI(t)) which is a function of time in the subject, The steps include converting the intracellular glucose concentration (GI(t)) into an HbA1c value, which is a function of blood cell age (H(i)), The steps include determining the erythrocyte age distribution (F(i)) associated with the aforementioned erythrocyte removal constant (K age), The process includes the step of assigning the HbA1c value to each red blood cell in the red blood cell age distribution (F(i)) according to the blood cell age (H(i)), thereby deriving the derived individual blood cell HbA1c distribution using the blood cell age (H(i)) and the red blood cell age distribution (F(i)). A method characterized by the following:

2. The step of measuring the plurality of first glucose levels is: A step of measuring the plurality of first glucose levels from bodily fluids collected from the subject using a sample sensor, Equipped with, The method performed by a computer according to feature 1.

3. The computer, the k gly The established standard k gly (K ref gly ) and the step of deriving a personalized target glucose range, a personalized glucose upper limit, and / or a personalized glucose lower limit based on the above, The computer diagnoses and / or monitors the subject based on the personalized target glucose range, the personalized upper glucose limit, and / or the personalized lower glucose limit. The method performed by a computer according to claim 1, further comprising the following:

4. The computer determines the k gly and the defined reference k gly (K ref gly ) to derive a personalized - target glucose range, a personalized glucose upper limit value, and / or a personalized glucose lower limit value; The computer displays an alert when the first glucose level is outside the personalized-target glucose range, above the personalized upper glucose limit, and / or below the personalized lower glucose limit. The method performed by a computer according to claim 1, further comprising the following:

5. The computer, the k gly The established standard k gly (K ref gly ) and the step of deriving a personalized target glucose range, a personalized glucose upper limit, and / or a personalized glucose lower limit based on the above, The computer displays the personalized target glucose range, the personalized upper glucose limit, and / or the personalized lower glucose limit. The method performed by a computer according to claim 1, further comprising the following:

6. The computer measures a plurality of second glucose levels for the subject over a second period, The computer derives a calculated HbA1c (cHbA1c) level for the subject based on the at least one physiological parameter and the plurality of second glucose levels, The method performed by a computer according to claim 1, further comprising the following:

7. The computer displays the cHbA1c level, The computer-based method according to claim 6, further comprising the above.

8. The computer, the cHbA1c level, the k age , and established standard k age (k ref age Based on, Formula 1 Using A step of calculating the adjusted HbA1c (aHbA1c) level for the subject, The computer-based method according to claim 6, further comprising the above.

9. The computer determines the cHbA1c level, the K, and the defined reference K (K ref Based on, Formula 2 Using A step of calculating the adjusted HbA1c (aHbA1c) level for the subject, The computer-based method according to claim 6, further comprising the above.

10. The computer receives the laboratory-measured HbA1c level for the subject, The computer determines the HbA1c level measured in the laboratory, and the k age , and established standard k age (k ref age Based on, Formula 3 Using The steps include calculating the adjusted HbA1c (aHbA1c) level for the subject, The method performed by a computer according to claim 1, further comprising the following:

11. The computer receives the laboratory-measured HbA1c level for the subject, The computer determines the laboratory-measured HbA1c level, the K, and the defined standard K (K ref Based on, Formula 4 Using The steps include calculating the adjusted HbA1c (aHbA1c) level for the subject, The method performed by a computer according to claim 1, further comprising the following:

12. It is a system, A sample sensor configured to measure glucose levels in body fluids, One or more processors, When operationally coupled with the one or more processors and executed by the one or more processors, A step of receiving a plurality of first glucose levels over a first period of time for a subject using the sample sensor, A step of receiving the HbA1c level of individual red blood cells in a sample of the subject's blood, which contains multiple red blood cells. A step of receiving the blood cell HbA1c distribution of the sample, wherein the blood cell HbA1c distribution is based on the HbA1c levels of individual red blood cells, A step of calculating at least one physiological parameter selected from the group consisting of (a) erythrocyte removal constant (k age), (b) erythrocyte glycation rate constant (k gly), and / or (c) apparent glycation constant (K), A memory that stores instructions for causing the system to perform a method comprising, The step of calculating the at least one physiological parameter is: The step includes generating the individual blood cell HbA1c distributions derived for the subject over the first period from a plurality of first glucose levels relating to the subject, The step of generating the individual blood cell HbA1c distributions of the subject over the first period from the plurality of first glucose levels relating to the subject is: A step of determining glucose (GI(t)) as a function of time in the subject based on the plurality of first glucose levels, The steps include converting the glucose (GI(t)) into an intracellular glucose concentration (GI(t)) which is a function of time in the subject, The steps include converting the intracellular glucose concentration (GI(t)) into an HbA1c value, which is a function of blood cell age (H(i)), The steps include determining the erythrocyte age distribution (F(i)) associated with the aforementioned erythrocyte removal constant (K age), The process includes the step of assigning the HbA1c value to each red blood cell in the red blood cell age distribution (F(i)) according to the blood cell age (H(i)), thereby deriving the derived individual blood cell HbA1c distribution using the blood cell age (H(i)) and the red blood cell age distribution (F(i)). A system characterized by the following features.

13. The aforementioned method, The aforementioned k gly The established standard k gly (K ref gly ) and the step of deriving a personalized target glucose range, a personalized glucose upper limit, and / or a personalized glucose lower limit based on the above, A step of displaying an alert when the first glucose level is outside the personalized-target glucose range, above the personalized upper glucose limit, and / or below the personalized lower glucose limit, It also has, The system according to feature 12.

14. The aforementioned method, The aforementioned k gly The established standard k gly (K ref gly ) and the step of deriving a personalized target glucose range, a personalized glucose upper limit, and / or a personalized glucose lower limit based on the above, A step of displaying the personalized target glucose range, the personalized upper glucose limit, and / or the personalized lower glucose limit on the system, It also has, The system according to feature 12.

15. The aforementioned method, A step of measuring multiple second glucose levels for the subject over a second period, A step of deriving a calculated HbA1c (cHbA1c) level for the subject based on the at least one physiological parameter and the plurality of second glucose levels, It also has, The system according to feature 12.

16. The aforementioned method, Steps to display the cHbA1c level on the system, It also has, The system according to claim 15, characterized in that it is the same as described above.

17. The aforementioned method, The cHbA1c level, the k age , and established standard k age (k ref age Based on, Formula 1 Using A step of calculating the adjusted HbA1c (aHbA1c) level for the subject, It also has, The system according to claim 15, characterized in that it is the same as described above.

18. The aforementioned method, The cHbA1c level, the K, and the defined standard K (K ref Based on, Formula 2 Using A step of calculating the adjusted HbA1c (aHbA1c) level for the subject, It also has, The system according to claim 15, characterized in that it is the same as described above.

19. A closed-loop insulin pump system, A sample sensor configured to measure glucose levels in body fluids, Insulin pump and One or more processors, When operationally coupled with the one or more processors and executed by the one or more processors, The step of receiving multiple glucose levels over time related to the subject using the aforementioned sample sensor, The step of receiving the HbA1c level of individual red blood cells in a blood sample of a subject containing multiple red blood cells. A step of receiving the blood cell HbA1c distribution of the sample, wherein the blood cell HbA1c distribution is based on the HbA1c levels of individual red blood cells in the sample, A step of calculating at least one physiological parameter selected from the group consisting of (a) erythrocyte removal constant (k age), (b) erythrocyte glycation rate constant (k gly), and / or (c) apparent glycation constant (K), and A step of administering an insulin dose through a closed-loop insulin pump system based on at least one of the aforementioned physiological parameters, A memory that stores instructions for causing the system to implement a method comprising, Equipped with The step of calculating the at least one physiological parameter includes generating the derived time-series distribution of individual blood cells HbA1c from a plurality of glucose levels relating to the subject, The step of generating the derived time-dependent HbA1c distribution of individual blood cells from the plurality of glucose levels is: A step of determining glucose (GI(t)) as a function of time in the subject based on the aforementioned multiple glucose levels, The steps include converting the glucose (GI(t)) into an intracellular glucose concentration (GI(t)) which is a function of time in the subject, The steps include converting the intracellular glucose concentration (GI(t)) into an HbA1c value, which is a function of blood cell age (H(i)), The steps include determining the erythrocyte age distribution (F(i)) associated with the aforementioned erythrocyte removal constant (K age), The process includes the step of assigning the HbA1c value to each red blood cell in the red blood cell age distribution (F(i)) according to the blood cell age (H(i)), thereby deriving the derived individual blood cell HbA1c distribution using the blood cell age (H(i)) and the red blood cell age distribution (F(i)). A closed-loop insulin pump system characterized by the following features.

20. The computer further comprises the step of diagnosing and / or monitoring the subject based on at least one of the physiological parameters. The method performed by a computer according to feature 1.

21. The red blood cell removal constant (k) is used until the derived individual blood cell HbA1c distribution matches the received blood cell HbA1c distribution. age ) and the red blood cell glycation rate constant (k gly ) adjust at least one of the following repeatedly The method implemented by the computer described in claim 1.

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